codemunch-pro
Intelligent code indexing MCP server. 13 tools, 10 languages, hybrid search, call graphs, O(1) symbol retrieval.
Install / Use
claude mcp add BigJai -- npx -y github:BigJai/codemunch-proIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
Development & EngineeringSupported Platforms
Tags
Our assessment of codemunch-pro
codemunch-pro scores 71/100 on our quality scale, 3818th of 4,658 Development & Engineering skills we index.
Its MCP Server is 4.3 KB long, well organised into 18 sections with 4 code examples: a solid amount of guidance for an agent.
It has 3 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 8 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 86/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
codemunch-pro compared with similar skills
All 4 of these similar skills score higher than codemunch-pro; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| codemunch-pro (this skill)by BigJai | 71 | 3 | 8mo ago | MCP Server |
| Agent-Reachby Panniantong | 100 | 106.6k | 5d ago | CLAUDE.md |
| taste-skillby Leonxlnx | 100 | 106.0k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.3k | today | CLAUDE.md |
| ai-job-searchby ai-job-search-dev | 100 | 67.6k | 3d ago | CLAUDE.md |
Frequently asked questions
- How do I install codemunch-pro?
- Run
claude mcp add BigJai -- npx -y github:BigJai/codemunch-pro. The install tabs above show the steps for each supported agent. - Which AI agents does codemunch-pro work with?
- It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
- Is codemunch-pro safe to use?
- It is MIT-licensed and scores 86/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is codemunch-pro still maintained?
- The repository was last updated about 8 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubCodeMunch Pro
<!-- mcp-name: io.github.BigJai/codemunch-pro -->Intelligent code indexing MCP server. 15 tools, 10 languages, tree-sitter AST extraction, hybrid search (FTS5 + vector), call graphs, remote repo indexing, incremental indexing.
Save 99% of tokens — get exact function source via byte-offset seek instead of reading entire files.
Install
pip install codemunch-pro
Quick Start
Claude Desktop / Cline
Add to your MCP client config:
{
"mcpServers": {
"codemunch-pro": {
"command": "codemunch-pro"
}
}
}
HTTP Server
codemunch-pro --transport streamable-http --port 5002
15 MCP Tools
| Tool | Description |
|------|-------------|
| index_folder | Index a local directory (incremental, SHA-256 based) |
| index_repo | Index a GitHub/GitLab repo (tarball download, no git needed) |
| list_repos | List all indexed repositories with stats |
| invalidate_cache | Force re-index a repository |
| file_tree | Get directory tree with file counts |
| file_outline | List symbols in a single file |
| repo_outline | List all symbols in repo (summary) |
| get_symbol | Get full source of one symbol (O(1) byte seek) |
| get_symbols | Batch get multiple symbols |
| search_symbols | Hybrid search (FTS5 + vector RRF) |
| search_text | Full-text search in file contents |
| get_callees | What does this function call? |
| get_callers | Who calls this function? |
| diff_symbols | What changed since last index? (PR review) |
| dependency_map | What does this file depend on? What depends on it? |
10 Languages
Python, JavaScript, TypeScript, Go, Rust, Java, C, C++, C#, Ruby
All via tree-sitter-language-pack — zero compilation, pre-built binaries.
Key Features
O(1) Symbol Retrieval
Every symbol stores its byte offset and length. get_symbol seeks directly to the function source — no reading entire files. A 200-byte function from a 40KB file = 99.5% token savings.
Incremental Indexing
Files are hashed (SHA-256). Only changed files are re-parsed. Re-indexing a 10K file repo after changing one file takes milliseconds.
Hybrid Search (FTS5 + Vector)
Combines BM25 keyword matching with semantic vector similarity using Reciprocal Rank Fusion. Search "authentication middleware" and find auth_middleware, verify_token, and login_handler.
Call Graphs
Traces function calls through the AST. get_callees("main") shows what main calls. get_callers("authenticate") shows who calls authenticate. Supports depth traversal.
Remote Repo Indexing (v1.1)
Index any public GitHub or GitLab repo by URL — no git binary needed. Downloads the tarball via API, extracts, and indexes. Cached locally with SHA-based freshness checks. Supports private repos with auth tokens and sparse paths.
Full-Text Content Search
Search raw file contents — string literals, TODO comments, config values, error messages. Not just symbol names.
How It Works
- Parse — tree-sitter builds an AST for each source file
- Extract — Walk AST to find functions, classes, methods, types, interfaces
- Store — SQLite database per repo with FTS5 virtual tables
- Embed — FastEmbed (ONNX, CPU-only) generates 384-dim vectors for semantic search
- Graph — Call expressions extracted from function bodies, edges stored and resolved
- Serve — FastMCP exposes 13 tools via stdio or HTTP
Architecture
~/.codemunch-pro/
├── myproject_a1b2c3d4e5f6.db # Per-repo SQLite database
├── otherproject_7890abcdef.db
└── ...
Each DB contains:
├── files # Indexed files with SHA-256 hashes
├── symbols # Functions, classes, methods, types
├── symbols_fts # FTS5 full-text search index
├── symbols_vec # sqlite-vec 384-dim vector index
├── call_edges # Call graph (caller → callee)
└── file_content_fts # Raw file content search
Use Cases
- AI Coding Agents: Give your agent surgical access to codebases without burning context
- Code Review: Find all callers of a function before changing its signature
- Onboarding: Search symbols semantically — "where is error handling?" finds relevant code
- Refactoring: Map call graphs before moving functions between modules
- Documentation: Extract all public APIs with signatures and docstrings
License
MIT
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headroom
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ai-job-search
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
