CGIS Code Graph MCP server

🧠 CGIS: Code Graph Intelligence System

<!-- mcp-name: io.github.zaebee/codegraph-brain -->

A code graph your AI agent can query instead of guess

Ask "what breaks if I change this?" and get the call chain, not a guess.

CGIS parses a repository with tree-sitter into a graph of fully qualified symbols and the calls, imports and containment between them, stores it in SQLite, and serves it to AI agents over MCP. An agent that would otherwise grep and read whole files asks the graph instead.

• Languages: Python · TypeScript / TSX
• Runs: locally — no account, no telemetry; the graph never leaves your disk (the one opt-in exception)

$ cgis ingest src --output graph.db
$ cgis impact cgis.query.engine.QueryEngine.get_flow_graph --db graph.db --depth 2
🔍 Analyzing transitive upstream callers of: cgis.query.engine.QueryEngine.get_flow_graph

METHOD cgis.query.engine.QueryEngine.get_flow_graph (cgis/query/engine.py:215)
├── FUNCTION cgis.query.context.context_service._collect_callees (cgis/query/context/context_service.py:44)
│   └── FUNCTION cgis.query.context.context_service.build_context (cgis/query/context/context_service.py:96)
└── METHOD cgis.guardian.collector.ContextCollector._graph_sections (cgis/guardian/collector.py:174)
    ├── METHOD cgis.guardian.collector.ContextCollector.collect_graph_context (cgis/guardian/collector.py:213)
    └── METHOD cgis.guardian.collector.ContextCollector.collect_for_chunk (cgis/guardian/collector.py:303)

Real output — CGIS run on its own source.

🚀 Quickstart

In Claude Code (fastest)

/plugin marketplace add zaebee/codegraph-brain
/plugin install cgis@codegraph-brain

That ships the MCP server, a skill that teaches the agent when to query the graph instead of reading files, and /cgis:ingest to build the graph on first use. The server is pulled from PyPI on demand via uvx, so there is nothing to clone or build.

Any other MCP client (Cursor, Claude Desktop, …)

{
  "mcpServers": {
    "cgis": { "command": "uvx", "args": ["--from", "codegraph-brain", "cgis-mcp"] }
  }
}

From the terminal

# No install needed — uvx fetches it from PyPI
uvx --from codegraph-brain cgis ingest ./my-project --output graph.db

uvx --from codegraph-brain cgis impact "my_module.core_function" --db graph.db --depth 5   # who calls this
uvx --from codegraph-brain cgis trace  "my_module.MyClass.run"   --db graph.db --depth 3   # what this calls
# add --format mermaid (or json) to either for a diagram or machine-readable output

Or install it for good: pip install codegraph-brain (Python 3.12+), then use cgis directly. The full command list is in CLI_USAGE.md.

📈 Proof at Real Scale

CGIS runs on a working twelve-repository estate — four languages, 8,146 commits, shipping daily. On its FastAPI backend it classifies 82.7% of 87,845 edges definitively and prints the remaining 17.3% rather than inventing targets for them — including the part that is CGIS's own gap.

Shortened. The full README is on GitHub.