AST knowledge graph plugin for Claude Code — semantic search, call graph, HTTP tracing, impact analysis
npx claudepluginhub sdsrss/code-graph-mcpAST knowledge graph for intelligent code navigation — auto-indexes your codebase and provides semantic search, call graph traversal, HTTP route tracing, and impact analysis via MCP tools
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Production-ready workflow orchestration with 79 focused plugins, 184 specialized agents, and 150 skills - optimized for granular installation and minimal token usage
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A high-performance code knowledge graph server implementing the Model Context Protocol (MCP). Indexes codebases into a structured AST knowledge graph with semantic search, call graph traversal, and HTTP route tracing — designed to give AI coding assistants deep, structured understanding of your code.
embed-model). Context reordered to prioritize structural relations over code for better embedding quality/understand, /trace, /impact), agents, skills, auto-indexing hooks, StatusLine integration, and self-updatingUnlike naive full-text search or simple AST dumps, code-graph-mcp builds a structured knowledge graph that understands the relationships between symbols across your entire codebase.
BLAKE3 Merkle tree tracks every file's content hash. On re-index, only changed files are re-parsed — unchanged directory subtrees are skipped entirely via mtime cache. When a function signature changes, dirty propagation automatically regenerates context for all downstream callers across files.
Combines BM25 full-text ranking (FTS5) with vector semantic similarity (sqlite-vec) via Reciprocal Rank Fusion (RRF) with raw score blending — so searching "handle user login" finds the right function even if it's named authenticate_session. Results are auto-compressed to fit LLM context windows.
The parser doesn't just find function calls — it tracks them within their proper scope context. Extracts calls, imports, inheritance, interface implementations, exports, and HTTP route bindings. Same-file targets are preferred over cross-file matches to minimize false-positive edges.
Unique to code-graph-mcp: trace from GET /api/users → route handler → service layer → database call in a single query. Supports Express, Flask/FastAPI, and Go HTTP frameworks.
Single binary, embedded SQLite, bundled sqlite-vec extension, optional local embedding model via Candle — no database server, no cloud API, no Docker required. Runs entirely on your machine.
Every design decision — from token-aware compression to node_id-based snippet expansion — is optimized for LLM context windows. Works out of the box with Claude Code, Cursor, Windsurf, and any MCP-compatible client.
| Metric | Value |
|---|---|
| Indexing speed | 300+ files/second (single-threaded, release build) |
| Incremental re-index | <250ms no-change detection via BLAKE3 Merkle tree |
| FTS search P50 / P99 | <300us / <1ms |
| Database overhead | ~3.5MB per 800 nodes |
| Token savings | 5-20x fewer tokens per code understanding task vs grep+read |
Run code-graph-mcp benchmark on your own project to measure.
Real-world benchmarks comparing code-graph-mcp tools against traditional approaches (Grep + Read + Glob) on a 33-file Rust project (~537 AST nodes).