smart-context-mcp

MCP server that reduces AI agent token usage by up to 90% through intelligent context compression (measured on this project).

What it is

An MCP (Model Context Protocol) server that provides specialized tools for reading, searching, and managing code context efficiently. Instead of loading full files or returning massive search results, it compresses information while preserving what matters for the task.

Real metrics from production use:

• ~7M tokens → ~800K tokens (approximately 89% reduction)
• 1,500+ operations tracked across development
• Compression ratios: 3x to 46x depending on tool
• Context overhead is tracked separately so reports can show gross and net savings

Workflow-level savings:

• Debugging: ~85-90% token reduction
• Code Review: ~85-90% token reduction
• Refactoring: ~85-90% token reduction
• Testing: ~85-90% token reduction
• Architecture: ~85-90% token reduction

Real adoption in non-trivial tasks:

• Approximately 70-75% of complex tasks use devctx tools
• Most used: smart_read (850+ uses), smart_search (280+ uses), smart_shell (220+ uses)
• Primary reasons for non-usage: task too simple, no index built, native tools preferred

See Workflow Metrics and Adoption Metrics for details.

Latest Release: 1.20.0

Minor release. Same 20 tools, but several gain new parameters and response fields. SQLite schema bumps 7 → 8 (new read_cache table; auto-migrates on first run). Global memory DB schema bumps 1 → 2 (new noise_hints table). Zero new runtime dependencies.

• Shared tokenBudget across tools. smart_read, smart_read_batch, smart_context, smart_turn (start + end) and smart_resume now accept tokenBudget: number | { id?, maxTokens, shared? }. When shared:true (or id set), the budget is reused across calls inside the same task — so a multi-step agent flow can stay under a hard token ceiling without per-call bookkeeping. Responses include taskBudget, remainingBudget, and budgetDetails (scope, actions, degraded mode) when the budget actually changed the output.
• smart_search search modes. New mode: 'needle' | 'balanced' | 'semantic' (default balanced). needle = literal exact only (no regex / no term expansion) — kills noise on debug queries. balanced = exact + regex + term expansion. semantic = exact-first plus the local semantic block only when exact signal is weak. The previous semantic: true flag remains as a legacy alias for mode: 'semantic'. Default maxFiles tightened 15 → 5. New maxTokens caps the whole response and compacts intelligently (matches first, then diagnostics, then semantic block). Per-file ranking is now inspectable via matchedBy, boostSource, scoreBreakdown, whyRanked. Response also returns hasMore / totalFiles / nextSuggestedMaxFiles and actionable suggestions when the query is too broad or empty.
• smart_read persistent cache + budget-aware full degradation. New SQLite read_cache table keyed by (filePath, mode, selector, content_hash). Second read of an unchanged file is virtually free. Mode full is now an explicit last resort: if a tokenBudget/maxTokens is set, it degrades to lighter modes first (outline → signatures → truncated) and reports the real mode used in fullMode + budgetDetails. New clearReadCachePersistent + GC integration in runStorageMaintenance.
• smart_turn simple-task skip heuristic. When the prompt is short (≤ 40 chars after normalization), classified as a simple task, and no session/task is pinned, smart_turn(start) now returns skipSmartTurn: true with recommendedPath.mode='simple_task_skip' instead of paying the full orchestration cost. Saves continuity-resolution overhead on trivial prompts. minimal verbosity additionally compacts summary/refreshedContext to the fields agents actually consume.
• global_memory noise hints. Per-project, scrubbed noise telemetry persisted to ~/.devctx/global.db (noise_hints table). New actions noise_stats and noise_reset (full or via query). Lets smart_search learn which queries the agent already discovered to be noisy in a given repo and adjust ranking, without ever leaking content.
• KPI baseline infrastructure. New scripts evals/kpi-baseline.js + evals/kpi-utils.js aggregate harness.js and realworld-eval.js runs into a single JSON snapshot with top-5 precision, recall, reread task/call rate, and per-task-size buckets (short / long). Persists kpi-baseline-latest.json for regression detection across releases. New test suite tests/eval-kpis.test.js.

Highlights from 1.19.0 (still current)

Five-step quality jump executed as sequential commits with full dogfooding. MCP grows from 18 → 20 tools, +68 tests, zero new dependencies, suite green at 882/883 (1 skipped).

• smart_playbook (new tool). Declarative composite workflows that run multiple smart_* tools in a single MCP call. Five built-in playbooks ship with the package: preflight-merge (review + affected tests + checkpoint), debug-flake (last failure + curated debug context + affected), refactor-safe (curated context + affected + checkpoint), doc-sync (ADR search + docs context), ramp-up (status + doctor + ADR overview). Project-level overrides via .devctx/playbooks/*.{yaml,json} with {{args.X}} interpolation, when / label / stopOnFail / dryRun. Tool allowlist restricted to smart_*. Zero deps: built-in minimal YAML parser.
• Reactive FS watcher for the index. fs.watch (native, recursive, debounced 600ms + batch flush every 2s) keeps the symbol index hot between calls. Filters .git, node_modules, .devctx, dist, build, lockfiles, .min.*, .map, .snap, and non-indexable extensions. Stats surface in smart_status (enabled, flushes, eventsObserved, filesReindexed, filesRemoved, errors, lastFlushAt, pending). Opt-out via DEVCTX_WATCH_INDEX=false. Wired to MCP shutdown for clean close + final flush.
• Richer Python / Go parsers + pluggable parser registry. Python now captures decorators (decorators: ["dataclass", ...]), async def (kinds async-function / async-method), TypeAlias and TypeVar / NewType / ParamSpec / TypeVarTuple as kind="type", and respects class indent for accurate scope. Go now captures methods with receiver type as parent, interfaces as kind="interface", top-level const / var. src/parsers/registry.js exposes registerParser / getParser so future tree-sitter parsers can plug in without touching index.js. INDEX_VERSION bumped 6 → 7 (auto-reindex).
• Local semantic re-rank on smart_search. Opt-in semantic: true (with semanticLimit) returns a semantic: { embedder, symbols[], files[] } block ranked by hashing/TF-IDF embeddings (256-dim, FNV-1a buckets, L2-normalized, cosine similarity, <5ms). Default behavior unchanged. Pluggable embedder interface (id, dimensions, embed, similarity) ready to swap in ONNX/transformers without touching callers.
• global_memory (new tool, opt-in). Cross-project memory persisted to ~/.devctx/global.db (override via DEVCTX_GLOBAL_DB, gated by DEVCTX_GLOBAL_MEMORY=true). Stores canonical decisions, recurring patterns, playbook drafts, and notes across repos. Content scrubbed for likely API keys / bearer tokens / JWT / PEM private keys / AWS / OpenAI / GitHub / Slack / Google API / DB URLs / emails / home paths before persistence. Project paths stored as FNV-1a hash, not raw path. Recall uses the local hashing/TF-IDF embedder for semantic ranking.

See CHANGELOG.md for the full v1.20.0 + v1.19.0 entries.

See CHANGELOG.md for full release history.

When to Use (and When Not To)

Use devctx when:

• You're exploring an unfamiliar codebase
• The task spans multiple sessions (checkpoints save context)
• You need to understand how files relate to each other (graph/imports)
• The context is too large to manage manually
• You're doing complex multi-file refactors or debugging across layers

Skip devctx when:

• You already know exactly which files to touch
• It's a single-file or surgical change (2-3 edits max)
• You have the full mental map from a recent exploration
• Native tools (Grep, Read, StrReplace) are more direct for the task

Honest verdict from real users:

"The MCP shines in long, multi-session tasks or when you don't know the codebase. For contained refactors where you already know what to touch, native tools are just as fast or faster. The real value was smart_read(outline) for the initial analysis and checkpoints to not lose the thread between sessions."

The 90% token savings are real, but they require the right task type to materialize.

Why it exists

AI agents waste tokens in three ways:

1. Reading full files when they only need structure or specific functions
2. Massive search results with hundreds of irrelevant matches
3. Repeating context across conversation turns

This MCP solves all three by providing tools that return compressed, ranked, and cached context.

🚨 Agent Ignored devctx? → Paste This Next

Use smart-context-mcp for this task.
Start with smart_turn(start), then use smart_context or smart_search before reading full files.
End with smart_turn(end) if you make progress.

Use devctx: smart_turn(start) → smart_context → smart_turn(end)

When to use: Agent read large files with Read, used Grep repeatedly, or you see no devctx tools in a complex task.

Why this happens: Task seemed simple, no index built, native tools appeared more direct, or rules weren't strong enough.

Quick Start: Which Client Should I Use?

🎯 Best Default: Cursor

Use if: You work in Cursor IDE and want the best balance of guidance and flexibility.

Workflow:

1. Install MCP → rules auto-load
2. Start task → agent reads .cursorrules
3. Agent decides when to use devctx
4. Use /prompt commands to force usage if needed

Automaticity: Medium by default. Medium-High if you use the assisted launcher ./.devctx/bin/cursor-devctx for task-runner workflows.

🔄 Best Continuity: Claude Desktop

Use if: You want highest session continuity with automatic context recovery.

Workflow:

1. Install MCP + hooks
2. Start task → hook auto-triggers smart_turn(start)
3. Work with devctx tools
4. End task → hook auto-triggers smart_turn(end)

Automaticity: High (with hooks) - Can auto-trigger smart_turn on session start/end.

💻 Best Terminal: Codex CLI / Qwen Code

Use if: You prefer terminal-based workflows or scripting.

Workflow:

1. Install MCP
2. Rules embedded in prompts
3. Agent reads rules, decides when to use
4. Explicit instructions work best

Automaticity: Low-Medium - Rules are visible but require explicit prompting.

📊 Quick Comparison

Important: Agent always decides whether to use devctx. Rules increase probability, but don't guarantee it.

If you want a more repeatable path: use the task runner or the assisted launcher instead of relying on rules alone. See Task Runner Workflows.

📖 Full setup: Client Compatibility

🚀 How to Invoke the MCP

Key point: The MCP doesn't intercept prompts automatically. You need to tell the agent to use it.

1️⃣ Use MCP Prompts (Easiest - Cursor only)

/prompt use-devctx

[Your task here]

Other prompts:

• /prompt devctx-workflow - Full workflow
• /prompt devctx-preflight - Build index + start session

2️⃣ Explicit Instruction (Any client)

Use smart_turn(start) to recover context, then [your task]

For a more guided CLI path:

smart-context-task task --prompt "your task"
smart-context-task implement --prompt "your task"
smart-context-task continue --session-id <session-id>
smart-context-task doctor

3️⃣ Automatic via Rules (Not guaranteed)

Agent should use devctx for complex tasks if rules are active:

• Cursor: .cursorrules
• Claude Desktop: CLAUDE.md
• Others: AGENTS.md

But: Agent decides based on task complexity.

⚡ Quick Reference

Recommended Workflow

✅ Setup Checklist (First Time in Project)

Before starting complex tasks, ensure:

# 1. MCP is installed
npm list -g smart-context-mcp  # or check your MCP client

# 2. Build the index (IMPORTANT)
npm run build-index
# or tell the agent: "Run build_index tool"

# 3. Rules are active
# - Cursor: .cursorrules exists
# - Claude Desktop: CLAUDE.md exists
# - Other clients: AGENTS.md exists

# 4. Start with smart_turn
# Tell the agent: "Use smart_turn(start) to begin"

Copy-paste to agent (first time):

Run build_index, then use smart_turn(start) to begin this task.

⚠️ Why Index Matters

Without index:

• ❌ smart_search returns unranked results
• ❌ smart_context can't build optimal context
• ❌ Agent may prefer native tools → no savings

With index:

• ✅ smart_search ranks by relevance
• ✅ smart_context includes related files
• ✅ 90% token savings enabled

When to rebuild:

• ✅ First time in project
• ✅ After major refactors (file moves, renames)
• ✅ After adding many new files
• ❌ Not needed every session (index persists in .devctx/)

The Entry Point: smart_turn(start)

For non-trivial tasks (debugging, review, refactor, testing, architecture), the optimal flow is:

0. build_index (if first time in project)
   ↓ enables search ranking and context quality
   
1. smart_turn(start, userPrompt, ensureSession=true)
   ↓ recovers previous context, classifies task, checks repo safety
   
2. smart_context(...) or smart_search(intent=...)
   ↓ builds context or finds relevant code
   
3. smart_read(mode=outline|signatures|symbol)
   ↓ reads compressed, cascades to full only if needed
   
4. [work: make changes, analyze, review]
   
5. smart_shell('npm test')
   ↓ verifies changes safely
   
6. smart_turn(end, event=milestone|blocker|task_complete)
   ↓ checkpoints progress for recovery

Why start with smart_turn?

• ✅ Recovers previous task checkpoint (goal, status, decisions)
• ✅ Classifies task continuation vs new task
• ✅ Provides repo safety check
• ✅ Enables task recovery if interrupted
• ✅ Tracks metrics for optimization

When to skip smart_turn:

• ❌ Trivial tasks (read single file, simple search)
• ❌ One-off questions (no continuity needed)
• ❌ Quick diagnostics (no session context)

The Product Entry Point: smart-context-task

If you want the same lifecycle packaged into named workflows, use the task runner:

smart-context-task task --prompt "inspect the auth flow and continue the bugfix"
smart-context-task implement --prompt "add a token guard to loginHandler"
smart-context-task review --prompt "review the latest diff"
smart-context-task doctor

This layer runs the same smart_turn(start) / context / checkpoint flow, but adds:

• workflow-specific preflight (smart_context or smart_search)
• continuity-aware prompt guidance
• blocked-state routing to smart_doctor
• measured task_runner quality signals

For the full command set and client-specific usage, see Task Runner Workflows.

How it Works in Practice

The Reality

This MCP does not intercept your prompts magically. Here's what actually happens:

1. You write a prompt: "Fix the login bug"
2. Agent reads rules: Sees debugging workflow suggestion
3. Agent decides: "This is a debugging task, I'll start with smart_turn(start)"
4. Agent calls: smart_turn({ phase: 'start', userPrompt: '...', ensureSession: true })
5. MCP returns: Previous task checkpoint (if exists) + repo safety check
6. Agent continues: Calls smart_search(intent=debug) for error location
7. Agent reads: Calls smart_read(mode=symbol) for specific function
8. Agent fixes bug: Makes changes
9. Agent verifies: Calls smart_shell('npm test')
10. Agent checkpoints: Calls smart_turn(end) to persist progress

Key points:

• ✅ Agent chooses to use devctx tools (not forced)
• ✅ Rules guide the agent (not enforce)
• ✅ smart_turn(start) is recommended entry point for non-trivial tasks
• ✅ Agent can skip workflow for trivial tasks
• ✅ You control nothing directly—the agent decides

What You Get

Tools (20): Efficient alternatives to built-in operations

• smart_read / smart_read_batch - Compressed file reading (outline, signatures, symbol, explain)
• smart_search - Intent-aware code search with ranking, ADR filtering, and opt-in semantic re-rank
• smart_context - One-call context builder with graph + paths: { from, to } traversal
• smart_test - Affected tests via graph + sandboxed runner + persisted last_failure
• smart_review - Code review preflight: diff + callers + heuristic findings
• smart_playbook - Declarative composite workflows (5 built-in: preflight-merge, debug-flake, refactor-safe, doc-sync, ramp-up)
• smart_shell - Safe diagnostic commands (TAP/git-log/diff compression)
• smart_turn / smart_resume - Session persistence + nextActions[] machine-readable plan
• smart_summary / smart_status / smart_doctor / smart_metrics / smart_edit
• global_memory - Opt-in cross-project memory in ~/.devctx/global.db (scrubbed, semantic recall)
• build_index / warm_cache / git_blame / cross_project

Rules (5 profiles): Task-specific workflows

• Debugging: Error-first, symbol-focused
• Code Review: Diff-aware, API-focused
• Refactoring: Graph-aware, test-verified
• Testing: Coverage-aware, TDD-friendly
• Architecture: Index-first, minimal-detail

Storage (.devctx/): Local context database

• index.json - Symbol index (functions, classes, imports, ADRs, sections) — INDEX_VERSION 7
• state.sqlite - Sessions, metrics, patterns, task handoffs, test failures, explain cache (Node 22+, node:sqlite)
• metrics.jsonl - Opt-in legacy file, only when DEVCTX_METRICS_FILE=path.jsonl is set
• ~/.devctx/global.db - Cross-project memory (opt-in via DEVCTX_GLOBAL_MEMORY=true)

Persistent Task Context (When Supported)

What gets persisted:

• Task checkpoints (goal, status, decisions, blockers)
• File access patterns (for prediction)
• Token metrics (for optimization)
• Session summaries (~100 tokens compressed)

When it's consulted:

• Agent calls smart_turn(start) - Recovers task checkpoint
• Agent calls smart_context - Uses patterns for prediction
• Agent calls smart_summary - Gets task summary

What is NOT persisted:

• ❌ Full conversation transcript
• ❌ Complete message history
• ❌ Agent reasoning or thoughts
• ❌ User prompts verbatim

Limitations:

• Only works if agent calls smart_turn (not automatic)
• Only persists within project (.devctx/ is local)
• Only recovers if session ID matches (manual or auto)
• Client must support MCP (Cursor, Codex, Claude Desktop, Qwen)

Honest truth: Task context persistence is opt-in via agent behavior, not automatic via client interception.

What This Means for You

Best case scenario:

• Agent follows rules consistently
• Uses devctx tools for 50-80% of operations
• Token usage drops 85-90% (proven, measured)
• Responses often faster due to less data to process (inferred from token savings)

Typical scenario:

• Agent uses devctx tools for complex tasks
• Uses built-in tools for simple tasks
• Token usage drops 60-80%
• Noticeable improvement in efficiency

Worst case scenario:

• Agent ignores rules (rare but possible)
• Uses built-in tools exclusively
• Token usage unchanged
• No harm done (MCP is passive)

You can check: npm run report:metrics shows actual tool usage and measured smart_turn quality signals.

What "Better Context" Means

What we improve:

• ✅ Context relevance (right files for the task)
• ✅ Signal-to-noise ratio (less boilerplate, more signal)
• ✅ Context efficiency (more relevant info in less space)
• ✅ Response speed (less data to process)

What we don't guarantee:

• ❌ Agent will always be correct
• ❌ Responses will be perfect
• ❌ Tasks will always succeed
• ❌ Responses will be "more accurate" (accuracy depends on agent, not just context)

The benefit: Agents work with better input, but output quality still depends on agent capability and task complexity.

Honest claim: We provide better context (more relevant, less noise), which can help agents respond more efficiently in complex tasks when the workflow is followed.

What's proven: 90% token savings (measured across 3,666 operations).
What's inferred: Quality improvement (better input → potentially better output, but not explicitly measured).
What we don't control: Agent correctness, task success, response accuracy.

Workflow Examples

Debugging

// 1. Start session
smart_turn({ 
  phase: 'start', 
  userPrompt: 'TypeError: Cannot read property "user" of undefined',
  ensureSession: true 
})
// → Recovers: "Last worked on auth system, checked validateToken()"

// 2. Find error
smart_search({ 
  query: 'TypeError user undefined',
  intent: 'debug'
})
// → Returns: src/auth.js (error handling), src/routes/login.js (recent change)

// 3. Read structure
smart_read({ 
  filePath: 'src/routes/login.js',
  mode: 'signatures'
})
// → Returns: loginHandler, validateCredentials, generateToken

// 4. Extract failing function
smart_read({ 
  filePath: 'src/routes/login.js',
  mode: 'symbol',
  symbol: 'loginHandler'
})
// → Returns: Full function code (250 tokens vs 5K for full file)

// 5. Reproduce error
smart_shell({ command: 'npm test -- login.test.js' })
// → Returns: Test failure output

// [Fix bug]

// 6. Verify fix
smart_shell({ command: 'npm test -- login.test.js' })
// → Returns: Tests pass

// 7. Checkpoint
smart_turn({ 
  phase: 'end',
  event: 'milestone',
  summary: 'Fixed TypeError in loginHandler - null check added',
  nextStep: 'Consider adding integration tests'
})

Token usage: 150K → 15K (90% savings)

Code Review

// 1. Start session
smart_turn({ 
  phase: 'start',
  userPrompt: 'Review PR #123 - Add JWT refresh token support',
  ensureSession: true
})

// 2. Get changed files context
smart_context({ 
  diff: true,
  detail: 'balanced'
})
// → Returns: Changed files with graph, prioritizes API surface

// 3. Review API surface
smart_read({ 
  filePath: 'src/auth.js',
  mode: 'signatures'
})
// → Returns: Exported functions only

// 4. Check implementation
smart_read({ 
  filePath: 'src/auth.js',
  mode: 'symbol',
  symbol: 'refreshToken'
})

// 5. Check authorship
git_blame({ 
  mode: 'symbol',
  filePath: 'src/auth.js'
})
// → Returns: Who wrote each function

// 6. Verify tests
smart_shell({ command: 'npm test' })

// 7. Checkpoint
smart_turn({ 
  phase: 'end',
  event: 'milestone',
  summary: 'PR #123 approved - JWT refresh implemented correctly',
  nextStep: 'Monitor production metrics after deploy'
})

Token usage: 200K → 25K (87% savings)

Refactoring

// 1. Start session
smart_turn({ 
  phase: 'start',
  userPrompt: 'Extract authentication logic into separate service',
  ensureSession: true
})

// 2. Build dependency graph
smart_context({ 
  entryFile: 'src/routes/login.js',
  detail: 'balanced'
})
// → Returns: Dependencies, imports, exports

// 3. Understand current structure
smart_read({ 
  filePath: 'src/routes/login.js',
  mode: 'signatures'
})

// 4. Extract target function
smart_read({ 
  filePath: 'src/routes/login.js',
  mode: 'symbol',
  symbol: 'validateCredentials'
})

// 5. Check authorship
git_blame({ 
  mode: 'symbol',
  filePath: 'src/routes/login.js'
})

// [Refactor: create src/services/auth.js, move logic]

// 6. Verify tests still pass
smart_shell({ command: 'npm test' })

// 7. Checkpoint
smart_turn({ 
  phase: 'end',
  event: 'milestone',
  summary: 'Extracted auth logic to AuthService - tests pass',
  nextStep: 'Update other routes to use AuthService'
})

Token usage: 180K → 20K (89% savings)

Testing

// 1. Start session
smart_turn({ 
  phase: 'start',
  userPrompt: 'Write tests for validateToken function',
  ensureSession: true
})

// 2. Find existing test patterns
smart_search({ 
  query: 'validateToken test',
  intent: 'tests'
})
// → Returns: Existing test files, test patterns

// 3. Read function to test
smart_read({ 
  filePath: 'src/auth.js',
  mode: 'symbol',
  symbol: 'validateToken'
})

// 4. Understand dependencies
smart_context({ 
  entryFile: 'src/auth.js',
  detail: 'minimal'
})
// → Returns: Dependencies (jwt, bcrypt, db)

// [Write test]

// 5. Run tests
smart_shell({ command: 'npm test -- auth.test.js' })

// 6. Checkpoint
smart_turn({ 
  phase: 'end',
  event: 'milestone',
  summary: 'Added 5 tests for validateToken - all pass',
  nextStep: 'Add edge case tests for expired tokens'
})

Token usage: 120K → 12K (90% savings)

Architecture Exploration

// 1. Start session
smart_turn({ 
  phase: 'start',
  userPrompt: 'Understand how authentication works in this codebase',
  ensureSession: true
})

// 2. Get high-level overview
smart_context({ 
  detail: 'minimal'
})
// → Returns: Project structure, key modules

// 3. Find auth-related code
smart_search({ 
  query: 'authentication authorization',
  intent: 'explore'
})
// → Returns: Ranked files by relevance

// 4. Review API surface
smart_read({ 
  filePath: 'src/auth.js',
  mode: 'signatures'
})
// → Returns: Exported functions only

// 5. Check cross-project patterns (if monorepo)
cross_project({ 
  mode: 'search',
  query: 'AuthService'
})
// → Returns: Similar auth patterns in other projects

// 6. Checkpoint
smart_turn({ 
  phase: 'end',
  event: 'milestone',
  summary: 'Auth uses JWT with 1h expiry, refresh tokens in Redis',
  nextStep: 'Document auth flow in architecture.md'
})

Token usage: 300K → 30K (90% savings)

Core Tools

These are the essential tools you should understand first:

smart_read

Read files in compressed modes instead of loading full content.

// Outline mode: structure only (~90% savings)
{ filePath: 'src/server.js', mode: 'outline' }

// Signatures mode: exported API only
{ filePath: 'src/api.js', mode: 'signatures' }

// Symbol mode: extract specific function/class
{ filePath: 'src/auth.js', mode: 'symbol', symbol: 'validateToken' }

Modes: outline, signatures, symbol, range, full

When to use: Any time you need to understand file structure without reading everything.

smart_search

Intent-aware code search with ranked, deduplicated results and index boosting.

// Find where a symbol is used
{ query: 'validateToken', intent: 'implementation' }

// Debug intent: prioritizes errors, logs, exception handling
{ query: 'authentication error', intent: 'debug' }

// Limit results
{ query: 'UserModel', maxFiles: 5 }

Intents: implementation, debug, tests, config, docs, explore

Best for: Finding symbol definitions/usages, understanding call chains, locating implementations.

NOT ideal for: Exact string matching (use Grep), finding files by name (use Glob), broad multi-word queries (generates noise — results include a hint when >30 files match).

smart_context

One-call context builder: search + read + graph expansion.

{
  task: 'Fix login authentication bug',
  detail: 'balanced'  // minimal | balanced | deep
}

Returns relevant files with compressed content, symbol details, and relationship graph.

Smart pattern detection: Automatically detects literal patterns in your task (TODO, FIXME, /**, console.log, debugger) and prioritizes them in search results.

When to use: Starting a new task and need comprehensive context.

build_index

Build a symbol index for the project (functions, classes, imports).

{ incremental: true }  // Only reindex changed files

When to use: Once after checkout, or after major changes. Improves search ranking and context relevance.

smart_metrics

Inspect token savings and usage statistics.

{ window: '24h' }  // or '7d', '30d', 'all'

When to use: Verify the MCP is working and see actual savings.

Advanced Tools

These tools provide specialized capabilities for specific workflows:

smart_summary

Maintain compressed task state across sessions.

// Save checkpoint (flat API - recommended)
{ action: 'update', goal: '...', status: 'in_progress', nextStep: '...' }

// Or nested format (backward compatible)
{ action: 'update', update: { goal: '...', status: 'in_progress', nextStep: '...' }}

// Resume later
{ action: 'get' }

Compresses task context to ~100 tokens (goal, status, decisions, blockers). Critical for long tasks. Supports both flat and nested formats. When git hygiene or SQLite health affects local state, responses also surface mutationSafety, repoSafety, degradedMode, and storageHealth.

smart_doctor

Run one operational preflight across repo hygiene, SQLite health, compaction, and legacy cleanup.

smart_doctor({})
smart_doctor({ verifyIntegrity: false })

Use this before release, after long-lived local usage, or whenever .devctx/state.sqlite looks suspicious.

smart_status

Display current session context with progress visibility.

{ format: 'detailed' }  // Full formatted output with emojis
{ format: 'compact' }   // Minimal JSON

Shows goal, status, recent decisions, touched files, pinned context, and progress stats. Updates automatically with each MCP operation. When repo safety or SQLite health affects state, smart_status stays useful via degraded mode and surfaces storageHealth plus the same mutationSafety contract as smart_turn.

smart_edit

Batch edit multiple files with pattern replacement.

{
  pattern: 'console.log',
  replacement: 'logger.info',
  files: ['src/a.js', 'src/b.js'],
  mode: 'literal'  // or 'regex'
}

Supports dryRun: true for preview. Useful for bulk refactoring, removing patterns, or renaming across files.

smart_turn

Orchestrate turn start/end with automatic task checkpoint recovery.

{ phase: 'start', prompt: '...' }  // Recovers task checkpoint
{ phase: 'end', event: 'milestone', update: {...} }  // Saves checkpoint

Recovers task state (goal, status, decisions, next step), not full conversation history.

smart_read_batch

Read multiple files in one call.

{
  files: [
    { path: 'src/a.js', mode: 'outline' },
    { path: 'src/b.js', mode: 'signatures' }
  ]
}

Reduces round-trip latency when you know you need several files.

smart_shell

Safe diagnostic command execution (allowlisted commands only).

{ command: 'git status' }

Blocks shell operators and unsafe commands by design.

Diff-Aware Context

Analyze git changes intelligently (part of smart_context):

{ task: 'Review changes', diff: 'main' }

Returns changed files prioritized by impact + related files (tests, importers).

Context Prediction

Learn from usage patterns and predict needed files (part of smart_context):

{ task: 'Implement authentication', prefetch: true }

After 3+ similar tasks: 40-60% fewer round-trips, 15-20% additional savings.

warm_cache

Preload frequently accessed files into OS cache.

{}  // No parameters

First query: 250ms → 50ms (5x faster cold start).

git_blame

Function-level code attribution.

// Who wrote each function?
{ mode: 'symbol', filePath: 'src/server.js' }

// Find code by author
{ mode: 'author', authorQuery: 'alice@example.com' }

// Recent changes
{ mode: 'recent', daysBack: 7 }

cross_project

Share context across monorepos and microservices.

// Search all related projects
{ mode: 'search', query: 'AuthService' }

// Find symbol across projects
{ mode: 'symbol', symbolName: 'validateToken' }

Requires .devctx-projects.json config file.

Client Compatibility

Legend:

• 🟢 High: Hooks can auto-trigger tools at specific moments
• 🟡 Medium/Low: Agent reads rules and decides when to use tools
• ✅ Supported | ⚠️ Partial | ❌ Not supported

What "Near-Automatic" Means

🟢 High (Claude Desktop with hooks):

• Hooks can auto-trigger smart_turn(start) when you start a session
• Hooks can auto-checkpoint after significant tool use
• Agent still decides which devctx tools to use for each task
• This is the closest to "automatic" behavior available

🟡 Medium (Cursor):

• Agent reads base rules automatically (always active, 150 tokens)
• Conditional profiles activate based on file globs (debugging, review, etc.)
• Agent decides when to use devctx tools based on task
• Agent must manually call smart_turn (not auto-triggered)

🟡 Low-Medium (Codex, Qwen):

• Agent reads embedded rules automatically (always active, 200 tokens)
• Agent decides when to use devctx tools based on task
• Agent must manually call smart_turn (not auto-triggered)
• No conditional activation or hooks

What "Near-Automatic" Does NOT Mean

❌ Not automatic prompt interception - MCP cannot intercept or modify your prompts before the agent sees them
❌ Not forced tool usage - Agent always has autonomy to decide which tools to use
❌ Not guaranteed workflow - Agent may skip devctx tools for simple tasks (this is fine)
❌ Not client-level magic - Behavior depends on agent following rules and making good decisions

The Reality

All clients work the same way:

1. Agent reads rules (guidance about when devctx tools are useful)
2. Agent decides tool usage (autonomy to choose best approach)
3. MCP provides tools (passive, only responds when called)
4. You verify with metrics (npm run report:metrics)

The differences:

• Hooks (Claude Desktop) can auto-trigger specific tools at specific moments (e.g., smart_turn(start) on session start)
• Conditional rules (Cursor) reduce fixed context cost and activate task-specific profiles when relevant
• Embedded rules (Codex, Qwen) are simple, always active, and work everywhere

Which Client Should I Use?

Choose Cursor if:

• ✅ You want lowest fixed context cost (150 tokens base + 120 tokens profile when active)
• ✅ You work on complex, multi-file tasks (debugging, refactoring, architecture)
• ✅ You want conditional rules that activate based on file patterns

Choose Claude Desktop if:

• ✅ You want closest to "automatic" behavior (hooks can auto-trigger smart_turn)
• ✅ You want session-aware workflows with automatic checkpointing
• ✅ You're okay with opt-in hook configuration

Choose Codex or Qwen if:

• ✅ You want simple, embedded rules (no separate config files)
• ✅ You prefer lightweight setup (single AGENTS.md file)
• ✅ You're okay with manual smart_turn calls and no conditional activation

Bottom line: All clients work well. The choice depends on your preference for automation level vs simplicity.

See Client Compatibility Guide for detailed comparison.

Installation

Step 1: Install the MCP Server

Minimal (Any Client)

npm install -g smart-context-mcp
npx smart-context-init --target .

Restart your AI client. Done.

Verify Installation

# Check installed version
npm list -g smart-context-mcp

# Should show: smart-context-mcp@1.20.0 (or later)

# Update to latest version
npm update -g smart-context-mcp

# Or reinstall from scratch
npm uninstall -g smart-context-mcp
npm install -g smart-context-mcp

After updating: The binary is updated globally, but agent rules (.cursorrules, CLAUDE.md, AGENTS.md) in each project are generated from the installed version and are not updated automatically.

Re-run init after each update to get the latest rules:

# Re-apply rules to a project after updating
npx smart-context-init --target /path/to/your/project --clients cursor
# or for all clients
npx smart-context-init --target /path/to/your/project --clients all

Then restart your AI client to load the new version.

Cursor

npm install -g smart-context-mcp
npx smart-context-init --target . --clients cursor

Restart Cursor. Tools appear in Agent mode.

Files created:

• .cursor/mcp.json - MCP server config
• .cursor/rules/devctx.mdc - Base agent rules (10 lines, always active)
• .cursor/rules/profiles-compact/*.mdc - Task profiles (conditional)
• .devctx/bin/cursor-devctx - Optional assisted launcher for long tasks
• .git/hooks/pre-commit - Safety hook
• .gitignore - Adds .devctx/

Codex CLI

npm install -g smart-context-mcp
npx smart-context-init --target . --clients codex

Restart Codex.

Files created:

• .codex/config.toml - MCP server config
• AGENTS.md - Agent rules
• .git/hooks/pre-commit - Safety hook
• .gitignore - Adds .devctx/

Claude Desktop

npm install -g smart-context-mcp
npx smart-context-init --target . --clients claude

Restart Claude Desktop.

Files created:

• .mcp.json - MCP server config
• .claude/settings.json - Hook config
• CLAUDE.md - Agent rules
• .git/hooks/pre-commit - Safety hook
• .gitignore - Adds .devctx/

Qwen Code

npm install -g smart-context-mcp
npx smart-context-init --target . --clients qwen

Restart Qwen Code.

Files created:

• .qwen/settings.json - MCP server config
• AGENTS.md - Agent rules
• .git/hooks/pre-commit - Safety hook
• .gitignore - Adds .devctx/

Agent Rules: The Secret Sauce

What makes this MCP different is task-specific agent guidance. Installation generates rules that teach agents optimal workflows:

Debugging Profile

smart_turn(start) → smart_search(intent=debug) → smart_read(symbol) → 
smart_shell('npm test') → fix → smart_turn(end)

Savings: 90% (150K → 15K tokens)

Code Review Profile

smart_turn(start) → smart_context(diff=true) → smart_read(signatures) → 
review → smart_turn(end)

Savings: 87% (200K → 25K tokens)

Refactoring Profile

smart_turn(start) → smart_context(entryFile) → smart_read(signatures) → 
refactor → smart_shell('npm test') → smart_turn(end)

Savings: 89% (180K → 20K tokens)

Testing Profile

smart_turn(start) → smart_search(intent=tests) → smart_read(symbol) → 
write test → smart_shell('npm test') → smart_turn(end)

Savings: 90% (120K → 12K tokens)

Architecture Profile

smart_turn(start) → smart_context(detail=minimal) → smart_read(signatures) → 
analyze → smart_turn(end)

Savings: 90% (300K → 30K tokens)

Key insight: The value isn't just in the tools—it's in teaching agents when and how to use them.

Step 2: Set Up Agent Rules (Recommended)

To ensure agents use devctx automatically, set up client-specific rules:

Cursor Users

Already included: .cursorrules is committed in the project.

Verify it's working:

• Agent should mention devctx usage policy
• Agent should use devctx tools automatically
• For long tasks, prefer ./.devctx/bin/cursor-devctx task --prompt "..." -- <agent-command>

Claude Desktop Users

Create CLAUDE.md in your project root:

# Copy template
cp docs/agent-rules-template.md CLAUDE.md
# Edit to keep only the CLAUDE.md section

Or copy the content from docs/agent-rules-template.md.

Other Agent Clients

Create AGENTS.md in your project root using the same template.

Why these rules matter:

• ✅ Agents use devctx automatically (no manual forcing)
• ✅ Consistent behavior across all clients
• ✅ Visible feedback when devctx is used
• ✅ Warnings when devctx should be used but isn't

See Agent Rules Template for complete setup.

Feedback When Not Used

If the agent doesn't use devctx tools in a non-trivial task, it will add a note:

Note: devctx not used because: [reason]
To use devctx next time: "Use smart-context-mcp: smart_turn(start) → ..."

Why this matters:

• Makes non-usage visible
• Educates about when devctx adds value
• Provides forcing prompt for next turn
• Identifies setup issues (MCP unavailable, index not built)

How to Force devctx Usage

When to use these prompts:

• Agent didn't use devctx in a non-trivial task
• You want to recover persisted task context
• Task is complex (debugging, review, refactor, testing, architecture)

Official prompt (complete workflow):

Use smart-context-mcp for this task:
1. Start with smart_turn(start, userPrompt, ensureSession=true) to recover context
2. Use smart_context or smart_search before reading files
3. Use smart_read(outline|signatures|symbol) instead of full reads
4. Close with smart_turn(end) when you reach a milestone

Ultra-short prompt (copy-paste ready):

Use devctx: smart_turn(start) → smart_context/smart_search → smart_read → smart_turn(end)

Example usage:

User: "Debug the authentication error"
Agent: [uses native tools]
Agent: "Note: devctx not used because: already had sufficient context..."

User: "Use devctx: smart_turn(start) → smart_context/smart_search → smart_read → smart_turn(end)"
Agent: [uses smart_turn, smart_search, smart_read]
Agent: "Found the issue in validateToken()..."

See agent-rules/ for complete profiles.

Getting Started

Day 1: Install + Build Index (Critical)

1. Install:

   npm install smart-context-mcp
   npx smart-context-init --target .
   

2. Build index (REQUIRED for quality):

   npm run build-index
   # or tell agent: "Run build_index tool"
   

   Why critical: Without index, smart_search and smart_context are degraded. Agent may prefer native tools. No token savings.

3. Use core tools:

   • smart_read for file structure
   • smart_search for finding code
   • smart_context for comprehensive context
   • smart_metrics to verify savings

4. Let the agent decide: Don't force tool usage. The generated rules will guide the agent naturally.

After 1 week: Add advanced tools

• smart_summary if you work on long tasks
• smart_turn if using Claude Code CLI
• git_blame for code attribution
• cross_project if working in monorepos

After 1 month: Optimize

• Check smart_metrics for usage patterns
• Enable warm_cache if cold starts are slow
• Enable prefetch in smart_context for repetitive tasks

Metrics & Verification

Run full benchmark

npm run benchmark

Runs all verification suites:

• 740+ unit tests
• 14 feature verifications
• Synthetic corpus evaluation
• Real project evaluation
• Orchestration regression benchmark (5 core scenarios)
• Production metrics report

Takes 3-4 minutes. See Benchmark Documentation for details.

Release gating for orchestration quality is also available with npm run benchmark:orchestration:release, and npm publish now blocks on that gate via prepublishOnly.

Check it's working

npm run report:metrics

Good signs:

• Tool usage > 0 (agent using devctx)
• Savings 60-90% (compression working)
• Multiple tools used (workflows followed)

Bad signs:

• Tool usage = 0 (agent not using devctx)
• Check: Rules installed? MCP running? Task complexity?

Example output:

devctx metrics report

Entries:      3,696
Raw tokens:   14,492,131
Final tokens: 1,641,051
Saved tokens: 13,024,099 (89.87%)

By tool:
  smart_search   count=692  saved=5,817,485 (95.45%)
  smart_read     count=2108 saved=2,355,809 (70.52%)
  smart_summary  count=449  saved=1,897,628 (97.89%)

Adoption Analysis (Inferred from Tool Usage)

Total sessions:        156
Sessions with devctx:  89 (57%)
Sessions without:      67 (43%)

Non-Trivial Tasks Only:
Total:                 112
With devctx:           78 (70%)
Without devctx:        34 (30%)

By Inferred Complexity:
- complex      56/68 (82%)
- moderate     25/52 (48%)
- simple       8/36 (22%)

When devctx IS used:
Avg tools/session:     2.8
Avg token savings:     146,337 tokens

Top Tools Used:
- smart_read            89 sessions
- smart_search          67 sessions
- smart_context         45 sessions

Limitations:
- Complexity inferred from operation count (not actual task complexity)
- Can only measure when devctx IS used (tool calls visible)
- Cannot measure feedback shown or forcing prompts (requires agent cooperation)
- Sessions without devctx may be simple tasks (not adoption failures)

Adoption Metrics (Experimental)

The metrics report now includes adoption analysis to measure how often devctx is actually used.

What we measure:

• ✅ Sessions with devctx tool usage (automatic, from tool calls)
• ✅ Adoption rate overall and by inferred complexity
• ✅ Top tools used per session
• ✅ Average token savings when devctx is used

What we DON'T measure:

• ❌ Feedback frequency (requires agent to report it)
• ❌ Feedback reasons (requires agent cooperation)
• ❌ Forcing prompt usage (can't detect from metrics)
• ❌ Actual task complexity (only inferred from operation count)

Limitations:

• Complexity is inferred (operation count), not actual
• Can only measure when devctx IS used (tool calls visible)
• Can't detect non-usage unless agent reports it
• Sessions without devctx may be simple tasks (not failures)

Why this is useful:

• See if devctx is being adopted in practice
• Identify patterns (complex tasks → higher adoption)
• Verify rules and onboarding are working
• Complement compression metrics with usage metrics

See Adoption Metrics Design for complete analysis.

Real-Time Usage Feedback (New!)

Get immediate visibility into devctx tool usage in every agent response.

ENABLED BY DEFAULT - Shows feedback after every devctx tool call.

Disable if too verbose:

export DEVCTX_SHOW_USAGE=false

What you'll see:

---

📊 **devctx usage this session:**
- **smart_read**: 3 calls | ~45.0K tokens saved (file1.js, file2.js, file3.js)
- **smart_search**: 1 call | ~12.0K tokens saved (query)

**Total saved:** ~57.0K tokens

*To disable this message: `export DEVCTX_SHOW_USAGE=false`*

Benefits:

• ✅ Know immediately if agent is using devctx
• ✅ See token savings in real-time
• ✅ Verify forcing prompts worked
• ✅ Debug adoption issues instantly

When to use:

• Verifying agent follows rules
• Debugging why devctx isn't used
• Measuring real-time impact
• Validating setup after installation

See Usage Feedback Documentation for complete guide.

Decision Explanations (New!)

Understand why the agent chose devctx tools and what benefits are expected.

ENABLED BY DEFAULT - Shows decision explanations for every devctx tool call.

Disable if too verbose:

export DEVCTX_EXPLAIN=false

What you'll see:

---

🤖 **Decision explanations:**

**smart_read** (read src/server.js (outline mode))
- **Why:** File is large (2500 lines), outline mode extracts structure only
- **Instead of:** Read (full file)
- **Expected benefit:** ~45.0K tokens saved
- **Context:** 2500 lines, 50000 tokens → 5000 tokens

**smart_search** (search "authentication" (intent: debug))
- **Why:** Intent-aware search prioritizes relevant results
- **Instead of:** Grep (unranked results)
- **Expected benefit:** ~12.0K tokens saved, Better result ranking

*To disable: `export DEVCTX_EXPLAIN=false`*

Benefits:

• ✅ Understand agent decision-making
• ✅ Learn when to use which tool
• ✅ Debug tool selection issues
• ✅ Validate agent is making good choices

When to use:

• Learning how devctx works
• Debugging why certain tools were chosen
• Validating agent behavior
• Understanding best practices

Combine with usage feedback for maximum visibility:

export DEVCTX_SHOW_USAGE=true
export DEVCTX_EXPLAIN=true

See Decision Explainer Documentation for complete guide.

Missed Opportunities Detection (New!)

Detect when devctx should have been used but wasn't.

ENABLED BY DEFAULT - Shows warnings when devctx adoption is low.

Disable if not needed:

export DEVCTX_DETECT_MISSED=false

What you'll see:

---

⚠️ **Missed devctx opportunities detected:**

**Session stats:**
- Duration: 420s
- devctx operations: 2
- Estimated total operations: 25
- devctx adoption: 8%

🟡 **low devctx adoption**
- **Issue:** Low devctx adoption: 2/25 operations (8%). Target: >50%.
- **Suggestion:** Agent may be using native tools. Consider forcing prompt.
- **Potential savings:** ~184.0K tokens

**How to fix:**
1. Use forcing prompt
2. Check if index is built
3. Verify MCP is active

Detects:

• 🔴 No devctx usage in long sessions (>5 min)
• 🟡 Low adoption (<30% of operations)
• 🟡 Usage dropped (no calls for >3 min)

Benefits:

• ✅ Identify adoption gaps
• ✅ Quantify potential savings
• ✅ Validate forcing prompts worked
• ✅ Detect when agent switches to native tools

Limitations:

• Total operations are estimated (not measured)
• May have false positives for simple tasks
• Session-scoped only (resets on restart)

All features enabled by default. To disable all:

export DEVCTX_SHOW_USAGE=false
export DEVCTX_EXPLAIN=false
export DEVCTX_DETECT_MISSED=false

See Missed Opportunities Documentation for complete guide.

Agent Rules (Multi-Client Support)

The project includes agent rules that enforce devctx usage across different clients:

• Cursor: .cursorrules (committed to git)
• Claude Desktop: CLAUDE.md (create from template in docs/agent-rules-template.md)
• Other agents: AGENTS.md (create from template in docs/agent-rules-template.md)

All rules enforce the same policy:

• Use smart_read instead of Read
• Use smart_search instead of Grep
• Use smart_context instead of multiple reads
• Explain if native tools are used

See Agent Rules Template for setup instructions.

MCP Prompts (Automatic Forcing)

The MCP server provides prompts that automatically inject forcing instructions:

Quick forcing:

/prompt use-devctx

This injects: Use devctx: smart_turn(start) → smart_context/smart_search → smart_read → smart_turn(end)

Available prompts:

• /prompt use-devctx - Ultra-short forcing prompt
• /prompt devctx-workflow - Complete workflow template
• /prompt devctx-preflight - Preflight checklist (index + session init)

Benefits:

• ✅ No need to remember/type forcing syntax
• ✅ Centrally managed (updates automatically)
• ✅ Discoverable in Cursor prompts menu
• ✅ No typos

See MCP Prompts Documentation for complete guide.

Quick verification

npm run verify  # Feature verification (20 tools)
npm test        # Unit tests (740+ tests)
npm run eval    # Synthetic corpus
npm run eval:self  # Real project

Troubleshooting

Agent not using devctx tools

Check:

# 1. Rules installed?
cat .cursor/rules/devctx.mdc

# 2. MCP running?
# Cursor: Settings → MCP → Check "smart-context" active

# 3. Index built?
ls .devctx/index.json

# 4. Metrics show usage?
npm run report:metrics

Possible causes:

• Rules not installed → Run npx smart-context-init --target .
• MCP not running → Restart client
• Index not built → Run npm run build-index or tell agent "Run build_index tool"
• Task too simple → Built-in tools sufficient (this is fine)
• Agent in Ask mode → Read-only, no MCP access

Force devctx usage (copy-paste ready):

Use devctx: smart_turn(start) → smart_context/smart_search → smart_read → smart_turn(end)

See How to Force devctx Usage for complete workflow.

Enable Workflow Tracking

To track complete workflows (debugging, review, refactor, testing, architecture):

export DEVCTX_WORKFLOW_TRACKING=true

Then restart your AI client. View workflow metrics:

npm run report:workflows -- --summary

See Workflow Metrics for details.

High token usage despite devctx

Check:

npm run report:metrics

Look for:

• Low tool usage (< 20% of operations)
• High full mode usage (agent not cascading)
• Low compression ratios (< 50%)

Possible causes:

• Agent not following workflows
• Task doesn't benefit from compression
• Rules unclear for this task type

Context not persisting

Check:

# 1. Node version (need 22+ for SQLite)
node --version

# 2. SQLite exists?
ls -lh .devctx/state.sqlite

# 3. Agent calling smart_turn?
sqlite3 .devctx/state.sqlite "SELECT COUNT(*) FROM sessions"

Possible causes:

• Node 18-20 → No SQLite (upgrade to 22+)
• Agent not calling smart_turn → No task checkpoints
• Session ID mismatch → Can't recover checkpoint
• .devctx/state.sqlite tracked/staged → runtime context writes are intentionally blocked until git hygiene is fixed
• .devctx/state.sqlite locked/corrupted/oversized → inspect storageHealth from smart_status or smart_metrics
• broader local-state preflight → run smart_doctor or smart-context-doctor --json

Recovery flow:

• missing → run a persisted action like smart_summary update or smart_turn end
• oversized → run smart_summary compact
• locked → stop competing devctx processes, then retry
• corrupted → back up .devctx/state.sqlite, remove it, and let devctx recreate local state

Rules not applied

Check:

cat .cursor/rules/devctx.mdc  # or AGENTS.md, CLAUDE.md

If missing:

npx smart-context-init --target .

If exists but agent ignores:

• This is expected (rules are guidance, not enforcement)
• Agent decides based on task
• Check metrics to see actual usage

Supported Languages

First-class (AST parsing): JavaScript, TypeScript, JSX, TSX

Heuristic parsing: Python, Go, Rust, Java, C#, Kotlin, PHP, Swift

Structural extraction: Shell, Terraform, HCL, Dockerfile, SQL, JSON, YAML, TOML

Configuration

Environment Variables

# Point to different project
export DEVCTX_PROJECT_ROOT=/path/to/project

# Disable cache warming
export DEVCTX_CACHE_WARMING=false

# Change warm file count
export DEVCTX_WARM_FILES=100

Cross-Project Setup

Create .devctx-projects.json:

{
  "version": "1.0",
  "projects": [
    { "name": "main-app", "path": ".", "type": "main" },
    { "name": "shared-lib", "path": "../shared-lib", "type": "library" },
    { "name": "api-service", "path": "../api-service", "type": "service" }
  ]
}

Build indexes for each project:

cd main-app && npx build-index
cd ../shared-lib && npx build-index
cd ../api-service && npx build-index

Storage

All data stored in .devctx/:

• index.json - Symbol index (INDEX_VERSION 7: ADR + ADR sections, richer Python/Go)
• state.sqlite - Sessions, metrics, patterns, task handoffs, test failures, explain cache (Node 22+)
• metrics.jsonl - Opt-in legacy file, only when DEVCTX_METRICS_FILE=path.jsonl is set

Cross-project (opt-in via DEVCTX_GLOBAL_MEMORY=true):

• ~/.devctx/global.db - Scrubbed decisions, patterns, playbooks, notes with semantic recall

Add to .gitignore:

.devctx/

Security

This MCP is secure by default:

• ✅ Allowlist-only commands - Only safe diagnostic commands (ls, git status, npm test, etc.)
• ✅ No shell operators - Blocks |, &, ;, >, <, `, $()
• ✅ Path validation - Cannot escape project root
• ✅ No write access - Cannot modify your code
• ✅ Repository safety - Prevents accidental commit of local state
• ✅ Resource limits - 15s timeout, 10MB buffer

What smart_shell can run:

# Allowed
git status              # ✓ Safe git read operations
npm test                # ✓ Safe package manager scripts
find . -name "*.js"     # ✓ File discovery
rg "pattern"            # ✓ Code search

# Blocked
git commit              # ✗ Write operations blocked
npm install pkg         # ✗ Package changes blocked
ls | grep secret        # ✗ Shell operators blocked
rm -rf /                # ✗ Dangerous commands blocked

Real rejection examples:

// Shell operator blocked
smartShell({ command: "ls | grep secret" })
→ { exitCode: 126, blocked: true, output: "Shell operators are not allowed..." }

// Dangerous command blocked
smartShell({ command: "rm -rf /" })
→ { exitCode: 126, blocked: true, output: "Dangerous pattern detected..." }

// Git write blocked
smartShell({ command: "git commit -m 'test'" })
→ { exitCode: 126, blocked: true, output: "Git subcommand not allowed: commit..." }

// Package install blocked
smartShell({ command: "npm install malicious" })
→ { exitCode: 126, blocked: true, output: "Package manager subcommand not allowed: install..." }

Verification:

# Run 60+ security tests to verify behavior
cd tools/devctx && npm test -- tests/smart-shell-security.test.js

Configuration:

# Disable shell execution entirely
export DEVCTX_SHELL_DISABLED=true

# Disable cache warming
export DEVCTX_CACHE_WARMING=false

Complete security documentation:

• SECURITY.md - Full security policy
• Security Rejection Examples - 50+ concrete examples

Requirements

• Node.js: 18+ (22+ recommended for SQLite features)
• Git: For diff-aware context and git blame
• ripgrep: Included via @vscode/ripgrep (no system install needed)

Performance Comparison

Documentation

Features

• Streaming Progress - Real-time progress notifications
• Context Prediction - Intelligent file prediction
• Diff-Aware Context - Smart change analysis
• Cache Warming - Cold-start optimization
• Git Blame - Code attribution
• Cross-Project Context - Multi-project support

Security

• Security Policy - Security guarantees and threat model
• Threat Model - Attack surface analysis
• Security Configuration - Hardening and profiles

Verification

• Benchmark - Reproducible benchmark
• E2E Test Report - Production usage analysis
• Verification Report - Feature verification
• Workflow Metrics - Complete workflow savings

Development

• Architecture - Repository structure and development guide
• Contributing - How to contribute
• Changelog - Version history

API Reference

Core Tools

smart_read

{
  filePath: string;
  mode?: 'outline' | 'signatures' | 'symbol' | 'range' | 'full';
  symbol?: string | string[];
  startLine?: number;
  endLine?: number;
  maxTokens?: number;
  context?: boolean;
}

smart_search

{
  query: string;
  intent?: 'implementation' | 'debug' | 'tests' | 'config' | 'docs' | 'explore';
  cwd?: string;
  maxFiles?: number; // 1-50, default 15
}

smart_context

{
  task: string;
  intent?: string;
  detail?: 'minimal' | 'balanced' | 'deep';
  maxTokens?: number;
  entryFile?: string;
  diff?: boolean | string;
  prefetch?: boolean;
  include?: string[];
}

build_index

{
  incremental?: boolean;
  warmCache?: boolean;
}

smart_metrics

{
  window?: '24h' | '7d' | '30d' | 'all';
  tool?: string;
  sessionId?: string;
}

Advanced Tools

smart_summary

{
  action: 'get' | 'update' | 'append' | 'checkpoint' | 'reset' | 'list_sessions';
  sessionId?: string;
  update?: {
    goal?: string;
    status?: 'planning' | 'in_progress' | 'blocked' | 'completed';
    nextStep?: string;
    completed?: string[];
    decisions?: string[];
  };
  maxTokens?: number;
}

smart_turn

{
  phase: 'start' | 'end';
  prompt?: string;
  event?: string;
  update?: object;
}

smart_read_batch

{
  files: Array<{
    path: string;
    mode?: string;
    symbol?: string;
  }>;
  maxTokens?: number;
}

smart_shell

{
  command: string;
}

warm_cache

{}  // No parameters

git_blame

{
  mode: 'symbol' | 'file' | 'author' | 'recent';
  filePath?: string;
  authorQuery?: string;
  limit?: number;
  daysBack?: number;
}

cross_project

{
  mode: 'discover' | 'search' | 'read' | 'symbol' | 'deps' | 'stats';
  query?: string;
  symbolName?: string;
  maxResultsPerProject?: number;
}

Core Capabilities

• ✅ 90% token reduction through intelligent compression
• ✅ Automatic orchestration with shared layer and client adapters
• ✅ Session continuity via SQLite state persistence
• ✅ Workflow tracking (debugging, code review, refactoring, testing, architecture)
• ✅ Task runner CLI with continuity-aware workflows
• ✅ Comparative metrics for cross-client benchmarking
• ✅ Production-ready with 740+ tests and release-gated benchmarks

See CHANGELOG.md for full release history.

Repository Structure

This repository contains the smart-context-mcp npm package in tools/devctx/:

/
├── tools/devctx/          ← Publishable package
│   ├── src/               ← Source code
│   ├── tests/             ← 740+ unit tests
│   ├── evals/             ← Benchmarks & scenarios
│   ├── scripts/           ← CLI binaries
│   └── package.json       ← Package metadata (v1.20.0)
├── docs/                  ← Documentation (GitHub only)
├── .github/workflows/     ← CI/CD with release gating
└── README.md              ← This file

What gets published to npm: Only tools/devctx/ contents (src + scripts)

Development: All work happens in tools/devctx/

See CONTRIBUTING.md for development setup.

Contributing

Pull requests welcome for:

• Additional language parsers
• Performance optimizations
• Bug fixes

See CONTRIBUTING.md for guidelines.

Author

Francisco Caballero Portero
Email: fcp1978@hotmail.com
GitHub: @Arrayo

License

MIT License - see LICENSE file for details.

Links

• GitHub Repository
• npm Package
• Issue Tracker