Indexes your codebase's public API surface at startup and serves it through five compact MCP tools: search by keyword, get exact signatures, pull full class references, view stats, and reindex incrementally. Supports C#, C++, Go, Java, Python, and TypeScript. Each result includes file paths and line numbers so Claude can do targeted reads instead of loading entire files. The benchmark shows 56–77% token reduction compared to grep-based workflows across real projects like vscode, Paper, and guava. Point it at any source directory with `--project`, add the CLAUDE.md snippet so the agent knows when to reach for it, and restart. Works best when paired with targeted Read calls using the returned line ranges.
MCP server that indexes your codebase's public API at startup and serves it via compact tool responses, saving tokens vs reading source files.
Parses source files, extracts public classes/methods/properties/fields/events, and serves them through 5 MCP tools. Works with Claude Code, Cursor, Windsurf, or any MCP-compatible AI tool.
Supported languages: C# (.cs), C++ headers (.h, .hpp, .hxx, .h++), Go (.go), Java (.java), Python (.py), TypeScript/JavaScript (.ts, .tsx, .js, .jsx)
Add to your .mcp.json:
{
"mcpServers": {
"codesurface": {
"command": "uvx",
"args": ["codesurface", "--project", "/path/to/your/src"]
}
}
}
Point --project at any directory containing supported source files (a Unity Assets/Scripts folder, a Spring Boot project, a .NET src/ tree, a Node.js/React project, a Python package, etc.). Languages are auto-detected.
Restart your AI tool and ask: "What methods does MyService have?"
Add this to your project's CLAUDE.md (or equivalent instructions file). This step is important. Without it, the AI has the tools but won't know when to reach for them.
## Codebase API Lookup (codesurface MCP)
Use codesurface MCP tools BEFORE Grep, Glob, Read, or Task (subagents) for any class/method/field lookup. This applies to you AND any subagents you spawn.
| Tool | Use when | Example |
|------|----------|---------|
| `search` | Find APIs by keyword | `search("MergeService")` |
| `get_signature` | Need exact signature | `get_signature("TryMerge")` |
| `get_class` | See all members on a class | `get_class("BlastBoardModel")` |
| `get_stats` | Codebase overview | `get_stats()` |
Every result includes file path + line numbers. Use them for targeted reads:
- `File: Service.cs:32` → `Read("Service.cs", offset=32, limit=15)`
- `File: Converter.java:504-506` → `Read("Converter.java", offset=504, limit=10)`
Never read a full file when you have a line number. Only fall back to Grep/Read for implementation details (method bodies, control flow).
| Tool | Purpose | Example |
|---|---|---|
search | Find APIs by keyword | "MergeService", "BlastBoard", "GridCoord" |
get_signature | Exact signature by name or FQN | "TryMerge", "CampGame.Services.IMergeService.TryMerge" |
get_class | Full class reference card with all public members | "BlastBoardModel" → all methods/fields/properties |
get_stats | Overview of indexed codebase | File count, record counts, namespace breakdown |
reindex | Incremental index update (mtime-based) | Only re-parses changed/new/deleted files. Also runs automatically on query misses |
search, get_signature, and get_class accept two optional filters:
file_path: scope results to a directory prefix or exact file (e.g. "src/services/" or "src/services/MergeService.ts")include_tests: include test files in results (default false). Detects __tests__/, tests/, test/, *.test.*, *.spec.*, *_test.*, test_*| Project | Language | Files | Records | Time |
|---|---|---|---|---|
| vscode | TypeScript | 6,611 | 88,293 | 9.3s |
| Paper | Java | 2,909 | 33,973 | 2.3s |
| client-go | Go | 219 | 2,760 | 0.4s |
| langchain | Python | 1,880 | 12,418 | 1.1s |
| pydantic | Python | 365 | 9,648 | 0.3s |
| guava | Java | 891 | 8,377 | 2.4s |
| immich | TypeScript | 919 | 7,957 | 0.6s |
| fastapi | Python | 881 | 5,713 | 0.5s |
| ant-design | TypeScript | 2,947 | 5,452 | 0.9s |
| dify | TypeScript | 4,903 | 5,038 | 1.9s |
| crawlee-python | Python | 386 | 2,473 | 0.3s |
| flask | Python | 63 | 872 | <0.1s |
| cobra | Go | 15 | 249 | <0.1s |
| gin | Go | 41 | 574 | <0.1s |
| Unity game (private) | C# | 129 | 1,018 | 0.1s |
Every record includes line_start and line_end (1-indexed). Multi-line declarations span the full signature:
[METHOD] com.google.common.base.Converter.from
Signature: static Converter<A, B> from(Function<...> forward, Function<...> backward)
File: Converter.java:504-506 ← multi-line signature
[METHOD] server.AlbumController.createAlbum
Signature: createAlbum(@Auth() auth: AuthDto, @Body() dto: CreateAlbumDto)
File: album.controller.ts:46 ← single-line
This lets AI agents do targeted reads instead of reading full files:
# Instead of reading the entire 600-line file:
Read("Converter.java") # 600 lines, ~12k tokens
# Read just the method + context:
Read("Converter.java", offset=504, limit=10) # 10 lines, ~200 tokens
Measured across 5 real-world projects in 5 languages, each using a 10-step cross-cutting research workflow.

| Language | Project | Files | Records | MCP | Skilled | Naive | MCP vs Skilled |
|---|---|---|---|---|---|---|---|
| C# | Unity game | 129 | 1,034 | 1,021 | 4,453 | 11,825 | 77% fewer |
| TypeScript | immich | 694 | 8,344 | 1,451 | 4,500 | 14,550 | 68% fewer |
| Java | guava | 891 | 8,377 | 1,851 | 4,200 | 26,700 | 56% fewer |
| Go | gin | 38 | 534 | 1,791 | 2,770 | 15,300 | 35% fewer |
| Python | codesurface | 9 | 40 | 753 | 2,000 | 10,400 | 62% fewer |

Even with follow-up reads for implementation detail, the hybrid MCP + targeted Read approach uses 44% fewer tokens than a skilled Grep+Read agent and 87% fewer than a naive agent:


See workflow-benchmark.md for the full step-by-step analysis across all languages.
By default, codesurface skips common vendored, build, and VCS directories: node_modules, vendor, bin, obj, dist, build, target, .git, .venv, __pycache__, and a few dozen others. Git worktrees and submodules are also skipped.
To exclude additional paths:
Project-level (committed): create a .codesurfaceignore file at your project root with one glob per line.
generated/**
docs/**
**/*.pb.go
Per-instance (CLI): pass --exclude with comma-separated globs.
{
"command": "uvx",
"args": ["codesurface", "--project", "src", "--exclude", "generated/**,vendor/**"]
}
Other indexing flags:
--include-submodules: index git submodules (skipped by default)--language <name>: pin to a single parser (e.g. --language cpp) instead of auto-detectingEach --project flag indexes one directory. To index multiple codebases, run separate instances with different server names:
{
"mcpServers": {
"codesurface-backend": {
"command": "uvx",
"args": ["codesurface", "--project", "/path/to/backend/src"]
},
"codesurface-frontend": {
"command": "uvx",
"args": ["codesurface", "--project", "/path/to/frontend/src"]
}
}
}
Each instance gets its own in-memory index and tools. The AI agent sees both and can query across projects.
Using pip install:
pip install codesurface
{
"mcpServers": {
"codesurface": {
"command": "codesurface",
"args": ["--project", "/path/to/your/src"]
}
}
}
codesurface/
├── src/codesurface/
│ ├── server.py # MCP server with 5 tools
│ ├── db.py # SQLite + FTS5 database layer
│ ├── filters.py # PathFilter (default exclusions, .codesurfaceignore, --exclude)
│ └── parsers/
│ ├── base.py # BaseParser ABC
│ ├── cpp.py # C++ header parser
│ ├── csharp.py # C# parser
│ ├── go.py # Go parser
│ ├── java.py # Java parser
│ ├── python_parser.py # Python parser
│ └── typescript.py # TypeScript/JavaScript parser
├── pyproject.toml
└── README.md
"No codebase indexed"
--project points to a directory containing supported source files (.cs, .h, .hpp, .go, .java, .py, .ts, .tsx, .js, .jsx)[codesurface] scanning N files... and [codesurface] done: linesServer won't start
python --version (needs 3.10+)mcp[cli] is installed: pip install mcp[cli]Stale results after editing source files
reindex() manually to force an incremental update