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17 MCP query tools for codebase navigation — functions, classes, imports, dependency graphs, change impact. Zero dependencies. 87% token reduction.

56 starsPython

MCP Codebase Index – 87% fewer tokens when AI navigates your codebase

by localforthewin·Feb 17, 2026·1 point·0 comments
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AI Analysis

●●●BangerSolve My ProblemBig BrainShip It

MCP query server cuts codebase context by 87% with zero dependencies, measured.

Strengths
  • •Incremental re-indexing via git diff (1–2ms overhead) keeps index fresh without manual triggers
  • •17 specialized query tools (functions, imports, dependency graph, change impact) vs. naive full-file reading
  • •Zero dependencies: pure stdlib ast module and regex, no external indexing library bloat
Weaknesses
  • •TypeScript support is regex-based, not AST—fragile for complex syntax and decorators
  • •Limited to Python, JS/TS, and Markdown; no C++, Java, or Go despite frequency in production codebases
Target Audience

Backend developers, full-stack engineers using Claude Code or Cursor

Similar To

Sourcegraph Cody · Continue.dev · Cursor's symbol indexing

Post Description

Built because AI coding assistants burn massive context window reading entire files to answer structural questions.

mcp-codebase-index parses your codebase into functions, classes, imports, and dependency graphs, then exposes 17 query tools via MCP.

Measured results: 58-99% token reduction per query (87% average). In multi-turn conversations, 97%+ cumulative savings.

Zero dependencies (stdlib ast + regex). Works with Claude Code, Cursor, and any MCP client.

pip install "mcp-codebase-index[mcp]"

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