Context7
by upstash
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Computer or cloud★ 64,224MITUpdated today
Install
Codemunch Pro
Overview
Description from the maker (original English)
Code indexing MCP: 15 tools, 10 languages, hybrid search, call graphs, O(1) retrieval.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Search & AI memory
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"codemunch-pro": {
"command": "uvx",
"args": [
"codemunch-pro"
]
}
}
}Run this in your terminal
claude mcp add codemunch-pro -- uvx codemunch-proOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"codemunch-pro": {
"command": "uvx",
"args": [
"codemunch-pro"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"codemunch-pro": {
"type": "stdio",
"command": "uvx",
"args": [
"codemunch-pro"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account BigJai, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7246 servers in this category
- Published to the registry more recently than 4% of the other 7246 servers in this category
- Basic checks equal to or better than 100% of the other 7246 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Codemunch Pro safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (1.2.0) reached the registry 8 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Context7, Codebase Memory, Exa
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Codebase Memory
by DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Runs on your computer★ 48,148MITUpdated 20 days ago
Install
Exa
by exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Runs in the cloud★ 5,213MITUpdated last month
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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-proQuick Start
Claude Desktop / Cline
Add to your MCP client config:
{"mcpServers": { "codemunch-pro": { "command": "codemunch-pro" } } }
HTTP Server
codemunch-pro --transport streamable-http --port 500215 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