CAT
/MCP
SkillsMCPMarketplacesDigestToolsAdvertise

This week in Claude

Every Monday: Claude Code, Agent SDK, MCP, and the Anthropic platform moves worth your time.

Skills by Category
Frontend DevelopmentBackend & APIsTesting & QASecurityDevOps & CI/CDGit & Pull RequestsDocumentationCode Review & QualityAI & Agent BuildingSkill Development
MCP Servers by Category
Sales & MarketingWeb & Browser AutomationDatabasesAI & LLM ToolsCloud & InfrastructureCommunication & MessagingDeveloper ToolsDesign & CreativeDocuments & KnowledgeSearch & Web Crawling
Marketplaces by Category
AI Agents & OrchestrationLLM IntegrationDevelopment ToolsFrontend & UIBackend & APIsDatabasesTesting & Code QualityDevOps & CloudSecurity & ComplianceGit & Version Control

Cross AI Tools

Discover Claude Code plugins, extensions, and tools. Automatically updated directory of Anthropic Claude AI marketplaces with development tools, productivity plugins, and integrations.

Resources

  • Browse Skills
  • Browse MCP Servers
  • Browse Marketplaces
  • Plugins Reference

Community

  • About
  • Tools
  • Feedback
  • Privacy Policy
  • Advertise

Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Cogmemai

hifriendbot/cogmemai-mcp
633 toolsauthSTDIO, HTTPregistry active
Summary

This is persistent memory for AI coding assistants that actually benchmarks at the top of the field: 95.10% on LongMemEval, 91% on LoCoMo. It exposes 35 MCP tools for saving memories, recalling by topic or semantic search, extracting principles from patterns, and auto-capturing coding sessions without requiring the AI to remember to save. Runs in cloud mode for full semantic search and team sync, local mode for offline-only setups, or hybrid for unreliable networks. Ships with quantum-safe encryption by default. Works across Claude Code, Cursor, Windsurf, Cline, and anything MCP-compatible. Reach for it when you're tired of re-explaining architectural decisions every session or watching your AI suggest approaches you already rejected three hours ago.

CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →

Tools

Public tool metadata for what this MCP can expose to an agent.

33 tools
save_memoryStore a developer memory (fact, preference, decision, architecture detail). Memories persist across all Claude Code sessions and are available in future conversations.9 params

Store a developer memory (fact, preference, decision, architecture detail). Memories persist across all Claude Code sessions and are available in future conversations.

Parameters* required
ttlstring
Set an expiration time. Use for temporary context like current task status. Format: "24h", "7d", "30d". Memory auto-archives after expiry.
tagsarray
Optional tags for grouping/threading memories (max 5 tags, each max 30 chars). E.g., ["marketing-campaign", "feb-2026"]
scopestring
global = applies everywhere, project = specific to this codebase, team = shared with team membersone of global · project · teamdefault: project
contentstring
The fact to remember (complete sentence)
subjectstring
What this is about, e.g. "auth_system", "react_version", "tab_width"default:
team_idinteger
Team ID (required when scope is "team"). The memory will be shared with all team members.
categorystring
Category: frontend, backend, database, devops, testing, security, performance, tooling, api, general. Custom categories also accepted for non-developer domains.default: general
importanceinteger
1-10 (10 = core architecture, 1 = trivial)default: 5
memory_typestring
Type: identity, preference, architecture, decision, bug, dependency, pattern, context. Custom types also accepted for non-developer domains.default: context
save_ruleSave a mandatory rule that will ALWAYS be followed in every session. Rules bypass scoring and decay — they are injected into every conversation, every time. Use for absolute requirements like "NEVER do X" or "ALWAYS do Y".5 params

Save a mandatory rule that will ALWAYS be followed in every session. Rules bypass scoring and decay — they are injected into every conversation, every time. Use for absolute requirements like "NEVER do X" or "ALWAYS do Y".

Parameters* required
tagsarray
Optional tags for grouping rules
scopestring
global = applies to all projects, project = only this codebaseone of global · projectdefault: project
contentstring
The rule to enforce (e.g., "NEVER use -latest model aliases", "ALWAYS apply changes to both class-chat.php AND class-maas.php")
subjectstring
Short label for the rule, e.g. "model_aliases", "companions_parity"default:
categorystring
Category for organization: frontend, backend, security, general, etc.default: general
list_rulesList all mandatory rules for the current project and/or globally. Rules are always-on memories that surface in every session.1 params

List all mandatory rules for the current project and/or globally. Rules are always-on memories that surface in every session.

Parameters* required
scopestring
Filter: all = project + global, project = this project only, global = global onlyone of all · project · globaldefault: all
delete_ruleDelete a mandatory rule by its memory ID. Use list_rules to find the ID first.1 params

Delete a mandatory rule by its memory ID. Use list_rules to find the ID first.

Parameters* required
memory_idinteger
The memory ID of the rule to delete
recall_memoriesSearch stored memories using semantic search. Returns memories ranked by relevance, importance, and recency. Use this to find relevant context from past sessions.10 params

Search stored memories using semantic search. Returns memories ranked by relevance, importance, and recency. Use this to find relevant context from past sessions.

Parameters* required
tagstring
Filter by tag (e.g., "marketing-campaign")
limitinteger
Max resultsdefault: 10
querystring
What to search for (natural language)
scopestring
Filter by scopeone of global · project · alldefault: all
team_idinteger
Optional override. Team memories are automatically included for team/enterprise users.
categorystring
Filter by category (e.g., "backend", "frontend", or any custom category)
synthesizeboolean
When true and 3+ results are found, returns an AI-synthesized summary combining all memories into a coherent answer.default: false
memory_typestring
Filter by typeone of identity · preference · architecture · decision · bug · dependency
context_typestring
Optional context type that shifts scoring weights. debugging = boost bug/pattern memories, planning = boost architecture/decision, reviewing = boost pattern/preference.one of debugging · planning · reviewing
importance_mininteger
Only return memories with importance >= this value
extract_memoriesExtract memories from a conversation exchange using AI. Send the developer message and assistant response, and the server identifies facts worth remembering (architecture decisions, preferences, bug fixes, etc.).3 params

Extract memories from a conversation exchange using AI. Send the developer message and assistant response, and the server identifies facts worth remembering (architecture decisions, preferences, bug fixes, etc.).

Parameters* required
user_messagestring
The developer's message
previous_contextstring
Previous exchange for context
assistant_responsestring
The assistant's response
get_project_contextLoad top memories for the current project plus relevant global memories. Use at the start of a session to get full context from previous sessions. Optionally pass context to get memories most relevant to your current task.7 params

Load top memories for the current project plus relevant global memories. Use at the start of a session to get full context from previous sessions. Optionally pass context to get memories most relevant to your current task.

Parameters* required
limitinteger
Max total memories to return (default 25). Lower values save context tokens.default: 25
compactboolean
When true (default), returns only formatted_context text instead of full JSON arrays. Saves ~60% tokens.default: true
contextstring
Optional context to improve relevance ranking (e.g., current task or topic)
team_idinteger
Optional override. Team memories are automatically included for team/enterprise users.
project_idstring
Project identifier (auto-detected from git remote if omitted)
context_typestring
Optional context type that shifts scoring weights. debugging = boost bug/pattern memories, planning = boost architecture/decision, reviewing = boost pattern/preference.one of debugging · planning · reviewing · general
include_globalboolean
Include global developer preferencesdefault: true
list_memoriesList stored memories with optional filters by type, category, scope, or project.9 params

List stored memories with optional filters by type, category, scope, or project.

Parameters* required
tagstring
Filter by tag (e.g., "marketing-campaign")
limitinteger
Results per pagedefault: 50
scopestring
Filter by scopeone of global · project · alldefault: all
offsetinteger
Pagination offsetdefault: 0
sort_bystring
Sort order: importance (default), updated, created, referenced (most used first), least_usedone of importance · updated · created · referenced · least_useddefault: importance
untypedboolean
When true, only return memories with no memory_type set
categorystring
Filter by category (e.g., "backend", "frontend", or any custom category)
memory_typestring
Filter by typeone of identity · preference · architecture · decision · bug · dependency
importance_mininteger
Only return memories with importance >= this value
delete_memoryDelete a specific memory by its ID. This is permanent.1 params

Delete a specific memory by its ID. This is permanent.

Parameters* required
memory_idinteger
Memory ID to delete
update_memoryUpdate an existing memory's content, importance, or scope.8 params

Update an existing memory's content, importance, or scope.

Parameters* required
tagsarray
New tags (replaces existing tags)
scopestring
New scopeone of global · project
contentstring
New content
subjectstring
New subject (e.g., "auth_system", "react_version")
categorystring
New category (e.g., "backend", "frontend", or any custom category)
memory_idinteger
Memory ID to update
importanceinteger
New importance (1-10)
memory_typestring
New memory typeone of identity · preference · architecture · decision · bug · dependency
bulk_deleteDelete multiple memories at once by their IDs. Maximum 100 IDs per call. This is permanent.1 params

Delete multiple memories at once by their IDs. Maximum 100 IDs per call. This is permanent.

Parameters* required
idsarray
Array of memory IDs to delete (max 100)
bulk_updateUpdate multiple memories at once. Each item needs a memory_id and fields to update. Maximum 50 items per call.1 params

Update multiple memories at once. Each item needs a memory_id and fields to update. Maximum 50 items per call.

Parameters* required
updatesarray
Array of update objects (max 50)
get_usageGet current usage statistics — memory count, extractions this month, tier info, projects.

Get current usage statistics — memory count, extractions this month, tier info, projects.

No parameter schema in public metadata yet.

export_memoriesExport all memories as JSON. Use this to back up memories or transfer them to another project.

Export all memories as JSON. Use this to back up memories or transfer them to another project.

No parameter schema in public metadata yet.

import_memoriesBulk import memories from a JSON array. Each memory needs at minimum a content field. Deduplication is applied automatically.1 params

Bulk import memories from a JSON array. Each memory needs at minimum a content field. Deduplication is applied automatically.

Parameters* required
memoriesstring
JSON string containing an array of memory objects. Each must have "content", optionally: memory_type, category, subject, importance, scope.
ingest_documentExtract memories from a document by splitting it into chunks and processing each one. Great for onboarding — feed in READMEs, architecture docs, or API specs to quickly build project context.2 params

Extract memories from a document by splitting it into chunks and processing each one. Great for onboarding — feed in READMEs, architecture docs, or API specs to quickly build project context.

Parameters* required
textstring
The document text to ingest (up to 50K characters)
document_typestring
Type hint for extraction (e.g., readme, api_docs, architecture, changelog)default: general
save_session_summarySave a summary of the current coding session. Captures what was accomplished, decisions made, and next steps. Stored as a session_summary memory for future reference.1 params

Save a summary of the current coding session. Captures what was accomplished, decisions made, and next steps. Stored as a session_summary memory for future reference.

Parameters* required
summarystring
Summary of the session — what was done, key decisions, and next steps
list_tagsList all tags in use across your memories, with counts. Use this to see what threads/groups exist and find related memories by tag.

List all tags in use across your memories, with counts. Use this to see what threads/groups exist and find related memories by tag.

No parameter schema in public metadata yet.

link_memoriesConnect two related memories with a named relationship. Use this to build a knowledge graph — e.g., linking a bug fix to the architecture decision that caused it, or connecting a preference to the pattern it led to.3 params

Connect two related memories with a named relationship. Use this to build a knowledge graph — e.g., linking a bug fix to the architecture decision that caused it, or connecting a preference to the pattern it led to.

Parameters* required
memory_idinteger
The source memory ID
relationshipstring
How the memories relate: led_to (A caused B), contradicts (A conflicts with B), extends (A builds on B), related (general connection)one of led_to · contradicts · extends · related
related_memory_idinteger
The target memory ID to link to
get_memory_linksView all memories linked to a specific memory. Returns the relationship type and full memory details for each connection. Use this to explore the knowledge graph around a memory.1 params

View all memories linked to a specific memory. Returns the relationship type and full memory details for each connection. Use this to explore the knowledge graph around a memory.

Parameters* required
memory_idinteger
The memory ID to get links for
get_memory_versionsView the edit history of a memory. Shows all previous versions with timestamps and what changed. Useful for understanding how a decision or fact evolved over time.1 params

View the edit history of a memory. Shows all previous versions with timestamps and what changed. Useful for understanding how a decision or fact evolved over time.

Parameters* required
memory_idinteger
The memory ID to get version history for
get_analyticsGet a memory health dashboard with insights: most recalled memories, never-recalled memories, stale memories, growth trends, and breakdowns by type and category. Use this to identify cleanup opportunities and understand memory usage patterns.1 params

Get a memory health dashboard with insights: most recalled memories, never-recalled memories, stale memories, growth trends, and breakdowns by type and category. Use this to identify cleanup opportunities and understand memory usage patterns.

Parameters* required
project_idstring
Filter analytics to a specific project. Omit for current project. Use "all" for cross-project analytics.
promote_memoryPromote a project-scoped memory to global scope so it applies across all projects. Use this when you discover a preference or pattern that should be universal — e.g., "user prefers tabs over spaces" or "always use Bun instead of npm".1 params

Promote a project-scoped memory to global scope so it applies across all projects. Use this when you discover a preference or pattern that should be universal — e.g., "user prefers tabs over spaces" or "always use Bun instead of npm".

Parameters* required
memory_idinteger
The project memory ID to promote to global scope
consolidate_memoriesConsolidate related memories into fewer, richer memories. Finds clusters of memories sharing the same subject (3+ memories required), then uses AI to synthesize each cluster into 1-2 comprehensive facts. Originals are archived (not deleted) with full version history. Use dry_r...4 params

Consolidate related memories into fewer, richer memories. Finds clusters of memories sharing the same subject (3+ memories required), then uses AI to synthesize each cluster into 1-2 comprehensive facts. Originals are archived (not deleted) with full version history. Use dry_r...

Parameters* required
dry_runboolean
When true, preview consolidation results without making changes. Recommended for first use.default: false
subjectstring
Consolidate only memories with this exact subject (e.g., "auth_system"). Omit to auto-detect all qualifying clusters.
categorystring
Only consolidate memories in this category
memory_typestring
Only consolidate memories of this typeone of identity · preference · architecture · decision · bug · dependency
save_taskCreate a task that persists across sessions. Tasks are tracked with status (pending, in_progress, done, blocked) and priority (high, medium, low). Use this to maintain continuity on multi-session work.4 params

Create a task that persists across sessions. Tasks are tracked with status (pending, in_progress, done, blocked) and priority (high, medium, low). Use this to maintain continuity on multi-session work.

Parameters* required
titlestring
Short task title (e.g., "Fix auth bug in login flow")
statusstring
Initial task statusone of pending · in_progress · done · blockeddefault: pending
prioritystring
Task priorityone of high · medium · lowdefault: medium
descriptionstring
Detailed description of what needs to be donedefault:
get_tasksGet tasks for the current project. Returns tasks filtered by status — defaults to showing pending and in_progress tasks. Use at session start to pick up where you left off.2 params

Get tasks for the current project. Returns tasks filtered by status — defaults to showing pending and in_progress tasks. Use at session start to pick up where you left off.

Parameters* required
statusstring
Filter by task status. "all" returns pending + in_progress + blocked (excludes done).one of pending · in_progress · done · blocked · alldefault: all
include_doneboolean
When true, also include completed tasksdefault: false
update_taskUpdate a task's status, title, description, or priority. Use this to mark tasks as in_progress, done, or blocked as you work.5 params

Update a task's status, title, description, or priority. Use this to mark tasks as in_progress, done, or blocked as you work.

Parameters* required
titlestring
New title
statusstring
New statusone of pending · in_progress · done · blocked
task_idinteger
The task memory ID (from get_tasks)
prioritystring
New priorityone of high · medium · low
descriptionstring
New description
save_correctionSave a correction pattern — what went wrong and what the right approach is. These are surfaced automatically when similar situations arise in future sessions, helping avoid repeated mistakes.4 params

Save a correction pattern — what went wrong and what the right approach is. These are surfaced automatically when similar situations arise in future sessions, helping avoid repeated mistakes.

Parameters* required
scopestring
global = applies everywhere, project = specific to this codebaseone of global · projectdefault: project
contextstring
When/where this applies (e.g., "package management in monorepo")default:
right_approachstring
The correct approach (e.g., "Always use bun add for this project")
wrong_approachstring
What was done incorrectly (e.g., "Used npm install instead of bun add")
set_reminderSet a reminder that surfaces automatically at the start of your next session. Use for follow-ups, things to check, or deferred work. Reminders auto-archive after being shown.2 params

Set a reminder that surfaces automatically at the start of your next session. Use for follow-ups, things to check, or deferred work. Reminders auto-archive after being shown.

Parameters* required
ttlstring
How long to keep the reminder alive. Format: "24h", "7d", "30d". Default: 7 days.default: 7d
contentstring
What to remind about (e.g., "Check if PR #42 was merged")
get_stale_memoriesFind memories that may be outdated based on age and access patterns. Returns memories that haven't been recalled or updated recently, so you can review, update, or delete them.2 params

Find memories that may be outdated based on age and access patterns. Returns memories that haven't been recalled or updated recently, so you can review, update, or delete them.

Parameters* required
limitinteger
Max results to returndefault: 20
days_thresholdinteger
Consider memories stale if not accessed in this many days (default: 30)default: 30
get_file_changesShow what files changed since your last session. Compares the current git state to a snapshot saved when your previous session ended. Helps you understand what happened between sessions.

Show what files changed since your last session. Compares the current git state to a snapshot saved when your previous session ended. Helps you understand what happened between sessions.

No parameter schema in public metadata yet.

feedback_memorySignal whether a recalled memory was useful or irrelevant. Helps improve future recall quality over time. Use after recalling memories to indicate which were helpful vs noise.2 params

Signal whether a recalled memory was useful or irrelevant. Helps improve future recall quality over time. Use after recalling memories to indicate which were helpful vs noise.

Parameters* required
signalstring
"useful" boosts the memory's ranking, "irrelevant" reduces its importance. For skills, "useful" boosts confidence, "irrelevant" reduces it.one of useful · irrelevant
memory_idinteger
The memory ID to give feedback on
generate_skillsManually trigger skill generation from your corrections, preferences, and patterns. Skills are behavioral directives that auto-improve how the AI works with you. CogmemAi also generates skills automatically when enough evidence accumulates — this tool lets you trigger it manua...3 params

Manually trigger skill generation from your corrections, preferences, and patterns. Skills are behavioral directives that auto-improve how the AI works with you. CogmemAi also generates skills automatically when enough evidence accumulates — this tool lets you trigger it manua...

Parameters* required
dry_runboolean
When true, preview skill candidates without generating themdefault: false
subjectstring
Generate skills for a specific subject. Omit to scan all subjects.
project_idstring
Project to generate skills for (auto-detected if omitted)

CogmemAi — Cognitive Memory for Any Ai System

npm version License: MIT Quantum Safe

CogmemAi — Cognitive Memory for Any Ai System

Autonomous robots. Self-driving vehicles. Defense systems. Coding assistants. Any Ai system that needs to remember.

CogmemAi demo — your Ai assistant remembers your project across sessions

CogmemAi is a portable memory layer that gives any Ai system persistent recall across sessions, devices, users, and teams — and captures knowledge autonomously, even when your Ai forgets to save. 95.10% accuracy on LongMemEval — top published score on the field's hardest long-term memory benchmark. 91% on LoCoMo, above human performance (87.9%). Quantum-safe encryption. Works with Claude Code, Cursor, Windsurf, Cline, Continue, and any MCP-compatible tool. Switch editors, switch models, switch machines — your knowledge stays. Not just one score on a test — the most complete Ai memory system available.

What's New in v3

Loud Failures on Firewall Blocks (v3.20.0)

When a request to the CogmemAi backend is intercepted by an upstream firewall, CDN, or proxy, the response is HTML, not JSON. Earlier versions tried to JSON-parse it and threw a confusing Unexpected token '<' error, then silently retried the same blocked payload. v3.20.0 detects HTML responses, names the blocking layer when it can (NinjaFirewall, Cloudflare, ModSecurity), and surfaces a clear actionable error. Retryable 4xx responses with HTML bodies no longer trigger retry loops. The class of incident that can silently drop memory writes is now loud.

Autonomous Memory — Your Ai Doesn't Decide Whether to Save Anymore (v3.15)

Every memory system has the same hidden failure mode: the Ai has to choose to save, and under pressure it doesn't. You can bake instructions into system prompts. You can nudge. But when your Ai is head-down on a coding task, it forgets to save — and the decisions you made two hours ago vanish when the context compacts.

CogmemAi v3.15 moves the decision out of the Ai's hands entirely. Your coding sessions are captured at the infrastructure level — decisions, file changes, bug fixes, and deployments land in memory without a single prompt. At session end, an intelligence pass distills them into structured memories: the right types, the right importance scores, the right scopes. Your Ai never sees this happen.

The result: a day of heavy coding produces 15–20 quality memories instead of 3. Future sessions pick up seamlessly. Your Ai stops re-litigating architectural choices you already made. Stop reminding your Ai to remember. It just does.

Proactive Memory Recall (v3.12)

CogmemAi now thinks before it speaks. Before your Ai assistant suggests any action, approach, or recommendation, CogmemAi checks its memory first — automatically, on every topic.

  • preflight tool — A fast, lightweight recall designed to be called before every suggestion. Your assistant checks what it already knows about a topic before opening its mouth. "Let's try approach X" → first checks if X was already tried, rejected, or completed. Sub-200ms, near-zero cost.
  • Prior context surfacing — Every time a memory is saved, CogmemAi automatically searches for related prior memories across all topics — people, companies, technical approaches, features, everything — and surfaces them in the response. Your assistant never suggests something redundant.
  • Smart recall hooks — In Claude Code, CogmemAi reads every user message and automatically injects relevant memories before the assistant responds. No manual recall needed — context arrives before the assistant starts thinking.
  • Upgraded recall engine — Higher-dimensional semantic understanding, balanced reranking, keyword-expanded search, dual-path memory storage for more reliable retrieval, and adaptive search that expands automatically when initial results are low confidence.

The result: your Ai assistant stops suggesting things you've already tried, people you've already contacted, and approaches you've already rejected. Your brain is no longer the safety net for what your tools should already know.

Wisdom Engine — Auto-Extracted Principles (v3.10)

CogmemAi now automatically detects patterns across your memories and extracts factual principles. While skills tell your Ai HOW to behave ("always use Zustand"), principles tell it what's TRUE about your project ("this codebase never validates inputs at service boundaries"). Principles are extracted from clusters of 5+ related memories, scored by confidence, and injected into every session. Use extract_principles to trigger manually or let it happen automatically.

Remote MCP — Zero Install (v3.9)

CogmemAi now supports Streamable HTTP transport — connect from any MCP client without installing anything. No npm, no config files, no Node.js required. Just point your client to https://hifriendbot.com/mcp/ with your API key and start using persistent memory immediately. Same 35 tools, same Intelligence Engine, same benchmark-topping accuracy — zero setup friction.

Quantum-Safe Encryption (v3.7)

CogmemAi is the first quantum-safe Ai memory system. All memories are encrypted at rest with quantum-resistant encryption — both in cloud mode and local mode. Your data is protected against today's threats and tomorrow's quantum computers. Encryption is automatic, zero-config, and enabled by default. No setup required.

Choose Your Storage Mode (v3.6)

CogmemAi now runs three ways — pick the one that fits your workflow:

Cloud (default)LocalHybrid
Best forFull intelligence, team collaboration, cross-device portabilityZero-config start, offline-only environmentsLocal speed + cloud brains, travel/unreliable networks
Setupnpx cogmemai-mcp setup (choose Cloud)npx cogmemai-mcp setup (choose Local)npx cogmemai-mcp setup (choose Hybrid)
API key neededYes (free)Yes (free) — like a license key, your data stays localYes (free)
SearchSemantic (by meaning)Full-text search (FTS5)Semantic with local fallback
Intelligence EngineFull — auto-linking, contradiction detection, memory decay, auto-skills, query synthesisFTS5 search + CRUD — data stays on your machineFull — with offline resilience
Team collaborationYesNoYes
Cross-device syncAutomaticNo — data stays on your machineAutomatic with local cache
Offline supportRequires internetFull offlineFalls back to local when offline
EncryptionQuantum-safe (server)Quantum-safe (local)Quantum-safe (both)

Cloud mode is the recommended experience. It gives you the full Intelligence Engine — semantic search that finds memories by meaning, auto-linking knowledge graph, contradiction detection, self-improving recall, auto-skills, query synthesis, and team collaboration. Everything that makes CogmemAi more than just a database.

Local mode keeps your data on your machine. A free API key is required for registration (like a software license key), but all your data stays local. Full-text search (FTS5) provides quality recall. Works offline after initial setup. When you're ready for semantic search and the full Intelligence Engine, upgrading to cloud takes one command.

Hybrid mode is for developers who travel or work on unreliable networks. Saves to both local and cloud simultaneously. Reads from cloud when available, falls back to local when offline. Unsynced memories automatically push to cloud when connectivity returns.

Intelligence Engine + Auto-Skills (v3.5)

CogmemAi now gets smarter every time you use it. The Intelligence Engine is a self-improving memory system that learns what matters, connects related knowledge automatically, and synthesizes answers from your entire memory. Auto-Skills takes it further — CogmemAi doesn't just remember, it learns how to behave.

Auto-Skills (Closed-Loop Learning)

  • Behavioral skills — CogmemAi automatically synthesizes your corrections, preferences, and patterns into behavioral directives that tell your Ai assistant HOW to work, not just what to know
  • Closed learning loop — correct your assistant once, and CogmemAi detects the pattern. After enough evidence accumulates, it generates a skill that prevents the mistake from ever happening again
  • Confidence tracking — each skill has a confidence score that rises when it works and drops when it doesn't. Low-confidence skills are automatically retired
  • Self-evaluation — skills periodically review themselves against new evidence and adapt, strengthen, or retire as your practices evolve

Intelligence Engine — 95.10% on LongMemEval, 91% on LoCoMo

CogmemAi scores 95.10% accuracy on LongMemEval — the top published score on the field's hardest long-term memory benchmark — and 91% accuracy on LoCoMo with a 100% retrieval hit rate, above human performance (87.9%). Two benchmarks, two #1-tier scores. CogmemAi finds the right memories when you need them.

  • Precision reranking — every recall runs a second-pass reranker that re-scores candidates for precision, balanced with the initial ranking signal to surface the most relevant memory first
  • Self-improving recall — memories that consistently help you rank higher over time; memories you never use fade naturally. Your recall quality improves automatically with every session
  • Auto-linking knowledge graph — related memories are automatically connected when you save them. Your knowledge builds into a web of relationships, not a flat list
  • Contradiction detection — when recalled memories conflict with each other, CogmemAi flags the contradiction so you catch stale or outdated information before it causes problems
  • Context-aware ranking — tell CogmemAi what you're doing (debugging, planning, reviewing) and it boosts the right types of memories. Debugging? Bug reports and patterns surface first. Planning? Architecture decisions lead
  • Query synthesis — ask a question and get one coherent answer synthesized from all your relevant memories, not just a list of matches. Like asking a teammate who's read everything
  • Cross-project intelligence — patterns that appear across 3+ projects are automatically promoted to global scope. Your best practices follow you everywhere without manual effort
  • Proactive insights — at session start, CogmemAi tells you what you should know before you ask. Stale critical memories, duplicate subjects that need merging, patterns ready for promotion

Also in v3

  • Memory health score — 0-100 score with actionable factors
  • Session replay — pick up exactly where you left off with automatic session summaries
  • Self-tuning memory — importance adjusts based on real usage; stale memories auto-archive
  • Auto-ingest README — learn from your README on new projects instantly
  • Smart recall — relevant memories surface automatically as you switch topics
  • Auto-learning — CogmemAi learns from your sessions automatically
  • Task tracking — persistent tasks with status and priority
  • Correction learning — teach your assistant to avoid repeated mistakes
  • Session reminders — nudges that surface at the start of your next session
  • Mandatory rules — define absolute requirements ("NEVER do X", "ALWAYS do Y") that surface in every session, bypassing all scoring and decay
  • Autonomous memory — captures work even when your Ai skips saves
  • 35+ tools — the most complete memory toolkit for any Ai system

Quick Start

Option 1: Remote (Zero Install)

Connect directly — no npm, no setup, no config files. Just add the remote endpoint to your MCP client with your API key:

Endpoint: https://hifriendbot.com/mcp/ Auth: Bearer token (your cm_ API key)

Get your free API key at hifriendbot.com/developer.

Works with any MCP client that supports Streamable HTTP transport (Claude Desktop, Cursor, and more).

Option 2: Local Install

npx cogmemai-mcp setup

The setup wizard walks you through three choices: Cloud (recommended — full Ai intelligence), Local (data stays on your machine), or Hybrid (both). Pick your mode, enter your API key if needed, and you're ready in under 60 seconds.

Don't have an API key yet? Get one free at hifriendbot.com/developer. Or choose Local mode to start immediately with no account.

The Problem

Every time you start a new session, you lose context. You re-explain your tech stack, your architecture decisions, your coding preferences. Built-in memory in tools like Claude Code is a flat file with no search, no structure, and no intelligence.

CogmemAi gives your Ai assistant a real memory system:

  • Semantic search — finds relevant memories by meaning, not keywords
  • Ai-powered extraction — automatically identifies facts worth remembering from your conversations
  • Smart deduplication — detects duplicate and conflicting memories automatically
  • Privacy controls — auto-detects API keys, tokens, and secrets before storing
  • Document ingestion — feed in READMEs and docs to instantly build project context
  • Project scoping — memories tied to specific repos, plus global preferences that follow you everywhere
  • Smart context — intelligently ranked for maximum relevance to your current work
  • Autonomous memory capture — saves knowledge even when your Ai forgets to call save. Decisions, file changes, and fixes land in memory without prompting
  • Compaction recovery — survives Claude Code context compaction automatically
  • Token-efficient — compact context loading that won't bloat your conversation
  • Zero setup — no databases, no Docker, no Python, no vector stores

Why Cloud Is the Recommended Mode

CogmemAi offers three storage modes, but cloud is where the magic happens. The Intelligence Engine — semantic search, auto-linking knowledge graph, contradiction detection, self-improving recall, auto-skills, and query synthesis — runs server-side. In cloud mode, your MCP server is a thin HTTP client with zero local databases, zero RAM issues, zero maintenance. All memories are encrypted at rest, so your data is just as secure as local storage — with cross-device portability and team features on top.

Your memory follows you everywhere. Memories created in Claude Code are instantly available in Cursor, Windsurf, Cline, and any MCP-compatible tool. Switch between Opus, Sonnet, Haiku, or any model your editor supports — your memories persist regardless. New laptop? New OS? Log in and your full project knowledge is waiting. A local SQLite file dies with your machine. Cloud memory is permanent.

The privacy argument is a myth. Some memory tools market "local-first" as a privacy advantage. But think about what happens next: every memory your Ai reads gets sent to the model provider (Anthropic, OpenAI, Google) as part of the prompt. Your data leaves your machine at inference time no matter where it's stored. A local SQLite file doesn't protect your memories — it just makes them harder to search, slower to access, and impossible to share. CogmemAi encrypts at rest, transmits over HTTPS, and adds intelligence that local storage simply can't match.

Teams and collaboration. Cloud memory is the only way to share project knowledge across teammates. When one developer saves an architecture decision or documents a bug fix, every team member's Ai assistant knows about it instantly. No syncing, no merge conflicts, no stale local databases. Whether it's two developers or twenty, everyone's assistant has the same up-to-date context. This is impossible with local-only memory solutions.

Compaction Recovery

When your Ai assistant compacts your context, conversation history gets compressed and context is lost. CogmemAi handles this automatically — your context is preserved before compaction and seamlessly restored afterward. No re-explaining, no manual prompting.

The npx cogmemai-mcp setup command configures everything automatically.

Skill

CogmemAi includes a Claude Skill that teaches Claude best practices for memory management — when to save, importance scoring, memory types, and session workflows.

Claude Code:

/skill install https://github.com/hifriendbot/cogmemai-mcp/tree/main/skill/cogmemai-memory

Claude.ai: Upload the skill/cogmemai-memory folder in Settings > Skills.

CLI Commands

npx cogmemai-mcp setup          # Interactive setup wizard
npx cogmemai-mcp setup <key>    # Setup with API key
npx cogmemai-mcp verify         # Test connection and show usage
npx cogmemai-mcp --version      # Show installed version
npx cogmemai-mcp help           # Show all commands

Manual Setup

If you prefer to configure manually instead of using npx cogmemai-mcp setup:

Option A — Per project (add .mcp.json to your project root):

{
  "mcpServers": {
    "cogmemai": {
      "command": "cogmemai-mcp",
      "env": {
        "COGMEMAI_API_KEY": "cm_your_api_key_here"
      }
    }
  }
}

For local mode (free API key required for registration, data stays local):

{
  "mcpServers": {
    "cogmemai": {
      "command": "cogmemai-mcp",
      "env": {
        "COGMEMAI_MODE": "local",
        "COGMEMAI_API_KEY": "cm_your_api_key_here"
      }
    }
  }
}

Option B — Global (available in every project):

# Cloud (default)
claude mcp add cogmemai cogmemai-mcp -e COGMEMAI_API_KEY=cm_your_api_key_here --scope user

# Local (free API key required, data stays local)
claude mcp add cogmemai cogmemai-mcp -e COGMEMAI_API_KEY=cm_your_api_key_here -e COGMEMAI_MODE=local --scope user

# Hybrid (both)
claude mcp add cogmemai cogmemai-mcp -e COGMEMAI_API_KEY=cm_your_api_key_here -e COGMEMAI_MODE=hybrid --scope user

Works With

Claude Code (Recommended)

Automatic setup:

npx cogmemai-mcp setup

Cursor

Add to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "cogmemai": {
      "command": "npx",
      "args": ["-y", "cogmemai-mcp"],
      "env": { "COGMEMAI_API_KEY": "cm_your_api_key_here" }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "cogmemai": {
      "command": "npx",
      "args": ["-y", "cogmemai-mcp"],
      "env": { "COGMEMAI_API_KEY": "cm_your_api_key_here" }
    }
  }
}

Cline (VS Code)

Open VS Code Settings > Cline > MCP Servers, add:

{
  "cogmemai": {
    "command": "npx",
    "args": ["-y", "cogmemai-mcp"],
    "env": { "COGMEMAI_API_KEY": "cm_your_api_key_here" }
  }
}

Continue

Add to ~/.continue/config.yaml:

mcpServers:
  - name: cogmemai
    command: npx
    args: ["-y", "cogmemai-mcp"]
    env:
      COGMEMAI_API_KEY: cm_your_api_key_here

CogmemUI

CogmemUI is a free multi-model Ai workspace with built-in CogmemAi memory. Add your CogmemAi API key in Settings > API Keys and your memory is instantly available. CogmemUI also supports connecting any MCP-compatible tool server via Settings > MCP Servers — add endpoints, auto-discover tools, and use them in chat.

Get your free API key at hifriendbot.com/developer.

Tools

CogmemAi provides 35 tools that your Ai assistant uses automatically:

ToolDescription
preflightProactive recall. Fast recall to check prior context before making any suggestion
save_memoryStore a fact explicitly (architecture decision, preference, etc.)
recall_memoriesSearch memories using natural language (semantic search)
extract_memoriesAi extracts facts from a conversation exchange automatically
get_project_contextLoad top memories at session start (with smart ranking, health score, and session replay)
list_memoriesBrowse memories with filters (paginated, with untyped filter)
update_memoryUpdate content, importance, scope, type, category, subject, and tags
delete_memoryPermanently delete a memory
bulk_deleteDelete up to 100 memories at once
bulk_updateUpdate up to 50 memories at once (content, type, category, tags, etc.)
get_usageCheck your usage stats and tier info
export_memoriesExport all memories as JSON for backup or transfer
import_memoriesBulk import memories from a JSON array
ingest_documentFeed in a document (README, API docs) to auto-extract memories
save_session_summarySave a summary of what was accomplished in this session
list_tagsView all tags in use across your memories
link_memoriesConnect related memories with named relationships
get_memory_linksExplore the knowledge graph around a memory
get_memory_versionsView edit history of a memory
get_analyticsMemory health dashboard with self-tuning insights (filterable by project)
promote_memoryPromote a project memory to global scope
consolidate_memoriesMerge related memories into comprehensive summaries using Ai
save_taskCreate a persistent task with status and priority tracking
get_tasksRetrieve tasks for the current project — pick up where you left off
update_taskChange task status, priority, or description as you work
save_correctionStore a "wrong approach → right approach" pattern to avoid repeated mistakes
set_reminderSet a reminder that surfaces at the start of your next session
get_stale_memoriesFind memories that may be outdated for review or cleanup
get_file_changesSee what files changed since your last session
feedback_memorySignal whether a recalled memory was useful or irrelevant to improve future recall
generate_skillsTrigger skill generation from your corrections and preferences — or preview candidates with dry run
save_ruleSave a mandatory rule that surfaces in every session — bypasses all scoring and decay
list_rulesList all mandatory rules for the current project and/or globally
delete_ruleDelete a mandatory rule by ID
extract_principlesTrigger Wisdom Engine to detect factual patterns across memory clusters

SDKs

Build your own integrations with the CogmemAi API:

  • JavaScript/TypeScript: npm install cogmemai-sdk — npm · GitHub
  • Python: pip install cogmemai — PyPI · GitHub

Memory Types

Memories are categorized for better organization and retrieval:

  • identity — Who you are, your role, team
  • preference — Coding style, tool choices, conventions
  • architecture — System design, tech stack, file structure
  • decision — Why you chose X over Y
  • bug — Known issues, fixes, workarounds
  • dependency — Version constraints, package notes
  • pattern — Reusable patterns, conventions
  • context — General project context
  • task — Persistent tasks with status and priority tracking
  • correction — Wrong approach → right approach patterns
  • reminder — Next-session nudges that auto-expire
  • rule — Mandatory directives that surface in every session, bypassing all scoring and decay

Scoping

  • Project memories — Architecture, decisions, bugs specific to one repo. Auto-detected from your repository.
  • Global memories — Your coding preferences, identity, tool choices. Available in every project.

Pricing

FreeProTeamEnterprise
Price$0$14.99/mo$39.99/mo$99.99/mo
Memories5002,00010,00050,000
Extractions/mo5002,0005,00020,000
Projects52050200

Start free. Upgrade when you need more. Or pay per operation with USDC on-chain — no credit card required.

Privacy & Security

  • 🛡️ Quantum-safe encryption at rest. All memories are encrypted with quantum-resistant cryptography — in cloud mode and local mode. Protected against both current threats and future quantum computers.
  • No source code leaves your machine. We store extracted facts (short sentences), never raw code.
  • API keys cryptographically hashed (irreversible) server-side.
  • All traffic over HTTPS.
  • No model training on your data. Ever.
  • Delete everything instantly via dashboard or MCP tool.
  • No cross-user data sharing.

Read our full privacy policy.

Environment Variables

VariableRequiredDescription
COGMEMAI_API_KEYCloud/HybridYour API key (starts with cm_). Not needed for local mode.
COGMEMAI_MODENoStorage mode: cloud (default), local (data stays on your machine), or hybrid
COGMEMAI_LOCAL_DBNoPath to local database (default: ~/.cogmemai/local.db). Used in local and hybrid modes.
COGMEMAI_API_URLNoCustom API URL (default: hifriendbot.com)
COGMEMAI_ENCRYPTION_KEYNoCustom encryption passphrase for local mode. If not set, a key is auto-generated.
COGMEMAI_LOCAL_ENCRYPTIONNoSet to off to disable local encryption (not recommended).

Support

  • Issues: GitHub Issues
  • Docs: hifriendbot.com/developer

License

MIT — see LICENSE


Built by HiFriendbot — Better Friends, Better Memories, Better Ai. 🛡️ Quantum Safe.

Featured
CodeRabbit
CodeRabbit
AI writes the code. CodeRabbit catches the slop.
Try For Free →
Keep your Mac awake
Keep your Mac awake
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →
Context.devContext.dev
Context.dev
Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →
Make your agent a DeFi expert
Make your agent a DeFi expert
Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →
Make money from your Skills
Make money from your Skills
On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
AppSignal
AppSignal
Monitor with ease. Code with confidence.
Start Free Trial →

Configuration

COGMEMAI_API_KEY*secret

Your CogmemAi API key from hifriendbot.com/developer/

Categories
AI & LLM Tools
Registryactive
Packagecogmemai-mcp
TransportSTDIO, HTTP
AuthRequired
UpdatedApr 22, 2026
View on GitHub

Related AI & LLM Tools MCP Servers

View all →
SkillFM LLM Cost Optimizer

io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage

LLM cost optimizer for OpenAI, Anthropic, token usage, BYOK, and SkillFM Beacon audits.
Llm Orchestration Agent

io.github.mikerawsonnz/llm-orchestration-agent

Run a prompt through a LangChain (system + human) chain over Gemini on Vertex AI; optional LangSmith
Authenticated Llm Agent

io.github.mikerawsonnz/authenticated-llm-agent

JWT-gated LLM gateway: authenticate (bcrypt/JWT), then run a LangChain-on-Vertex Gemini completion.
Copilot Memory MCP

labforgedev/copilot-memory-mcp

Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
1
Agent Prompt Injection Firewall Mcp

csoai-org/agent-prompt-injection-firewall-mcp

The WAF for agents. Pattern-based + heuristic firewall scans prompts, RAG documents, tool argume...
Authenticated Multi Llm Agent

io.github.mikerawsonnz/authenticated-multi-llm-agent

Google-OAuth-gated LLM gateway: verify a Google ID token, then run a Gemini (Vertex AI) completion f