Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
Code graph for coding agents: symbol search, callers, blast radius and cross-service impact.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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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": {
"cgraph": {
"command": "npx",
"args": [
"-y",
"cgraph-mcp"
]
}
}
}Run this in your terminal
claude mcp add cgraph -- npx -y cgraph-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"cgraph": {
"command": "npx",
"args": [
"-y",
"cgraph-mcp"
]
}
}
}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.
Paste into .vscode/mcp.json in your project
{
"servers": {
"cgraph": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cgraph-mcp"
]
}
}
}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.
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Runs on your computer; the tool list appears in your AI app after you install it.
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
The registry name was verified with the GitHub account Nxtsoft, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
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.
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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).
The GitHub repo last changed –, and the latest version (0.9.7) reached the registry 16 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
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
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
English · 简体中文
*Scan a project · extract structure into a deterministic graph · query it in ~10 ms from a daemon, a thin client, or an MCP server.*
Why CGraph? · Architecture · Repository layout · What it produces · Output formats · Performance · Retrieval benchmark · Languages · Quick start · Install & Setup · Use with coding agents · CLI · daemon · MCP reference · Host integrations & enrichment · Development notes · Contributing · License
Reading a large repo to answer "what calls this?" or "what breaks if I change it?" means loading dozens of files — and those answers aren't in any single file. They live in the *relationships between* files. CGraph precomputes them so you (and your AI agent) navigate by graph, not grep.
| 🔗 Reverse dependencies & blast radius | graph_impact returns every transitive dependent of a symbol in ~10 ms. On a real 10,706-node repo it surfaced 93 dependents of one god-file, instantly — an answer grep can't give you. |
| 🧭 Navigate, don't grep | Centrality-ranked search, node neighborhoods, shortest paths, and token-budgeted source bundles — served warm in ~10 ms instead of many file reads that burn context. |
| 🏛️ Architecture at a glance | Centrality ranking surfaces the load-bearing files; Leiden/Louvain community detection clusters the repo into modules automatically. |
| ⚡ Deterministic & fast | A full 10k-node graph builds in ~2 s; no LLM in the extraction path — same input, same graph, every time. |
| 🤖 Built for coding agents | A standard MCP server drops the graph straight into Claude / Codex, so they reason over structure instead of blindly reading files. |
The pitch in one line: for a codebase too big to hold in your head, CGraph is the index that decides *which* code to read —
ctags/"find all references", precomputed, centrality-ranked, and exposed over MCP.
graph.json, graph.html, graph.svg, obsidian.md, cypher.txt, modules.mmd, modules.svg, design.mmd, design.md).query / path / explain / impact / context in ~10 ms.The engine owns deterministic extraction, fragment validation, cache state, and local graph mutation; hosts own model choice and semantic enrichment.
src/cli/ One-shot CLI entrypoint: cgraph
src/daemon/ Daemon entrypoint: graphd src/client/ Thin client runtime and cgraph-client executable src/mcp/ MCP request handling and cgraph-mcp executable src/engine/ Detection, extraction, graph building, analysis, daemon ops tests/smoke/ CTest smoke coverage for engine, daemon, MCP, and integration paths tests/fuzz/ Optional libFuzzer targets integrations/ Host hook and always-on integration scripts docs/ Host integration contract and benchmark notes vendor/ Vendored tree-sitter core and grammars
A single scan turns a source tree into an interactive, explorable graph — communities colored, hubs sized by centrality:
The real graph.html viewer on a 10,708-node / 28,945-edge codebase — self-contained HTML, no external JS.
graph.json — directed node-link JSON with graph metadata, nodes, and links. Node ids derive from each file's path relative to the project root, so the same commit built from two checkouts yields the same ids and two graphs can be joined by id; source_file stays the path the graph was read fromgraph.html — browser-readable interactive graph viewgraph.svg — static graph visualizationobsidian.md — markdown export for Obsidian-style navigationcypher.txt — Neo4j Cypher statementsmodules.mmd — module dependency diagram as Mermaidmodules.svg — module dependency diagram as a layered static imagedesign.mmd — entry points and their top call flows as a Mermaid flowchart TDdesign.md — the same as Markdown: entry-point table, nested flows, layers by call distanceThe interactive viewer used to run an O(N²) force simulation in the browser on every open. Layout is now precomputed once in C++ (via igraph), and repaints are viewport-culled — both dependency-free:
| graph | time-to-settle before | after | per-frame repaint |
|---|---|---|---|
| 10,000 nodes | 35.2 s (main thread pinned) | ~0 ms (static layout) | 20–34× cheaper (zoom/pan) |
CGraph has been scored on Agent Retrieval Bench: 427 samples from 25 repositories, each checked out at its base commit, scored with the benchmark's own metric code. The table covers all 345 positive samples.
| Method | Recall@20 | MRR | BCY@8k |
|---|---|---|---|
| CGraph bin-v0.9.1 (label + code-text search) | 0.6362 | 0.2787 | 0.4319 |
| CGraph bin-v0.8.3 (label-only text search) | 0.5726 | 0.2356 | 0.3790 |
| RepoMap (published) | 0.6333 | 0.2158 | 0.3788 |
| RepoMap (rerun on this harness) | 0.6311 | 0.2156 | 0.3846 |
| Qwen3-Embedding-8B (published) | 0.7029 | 0.2336 | 0.3732 |
| Qwen3-Embedding-4B (published) | 0.6306 | 0.2379 | 0.3409 |
| BM25 (published) | 0.4452 | 0.1520 | 0.2051 |
How bin-v0.9.1 compares:
Per-task tables, pins, the noise floor and caveats are in bench/arb/RESULTS.md. Reproduce with bench/arb/run.sh.
Tree-sitter-backed structural extraction, with regex/structured extraction for a few config formats:
Plus structured/regex extraction for Apex, Delphi form/source, MSBuild/XML project files, and MCP config files.
Seven languages emit a field node per declared member, with a defines edge from the owner:
| Language | Owners with members | Field properties |
|---|---|---|
| C, C++ | class, struct only — not enum or union | none |
| TypeScript, TSX | interface, object type alias, class (constructor parameter properties included), enum | type_text, optional, readonly |
| Go | struct, including multi-name and embedded fields | type_text |
| Rust | named and tuple struct, union, enum variant, trait associated type and constant | type_text |
| Python | class-body assignment, including chained and tuple targets | type_text when annotated |
| Java | class, record, enum | type_text, readonly |
Members are declared members only: no inherited-member expansion, no alias flattening, no runtime attribute inference. A declaration that is already a node of its own — a TypeScript method_signature, a Rust trait method or type alias — keeps its function or type node and is not also a field. A field never takes the id a function or type holds; it moves instead, so a symbol's id stays stable.
A class-like declaration without a body (struct FileCacheEntry;) is a forward declaration and mints no node; only the body-bearing definition does.
Fields are members, not navigation targets: graph_context packs the owner (whose snippet spans its members) rather than the members, and report modules symbol counts exclude them.
JavaScript and TypeScript services get one endpoint node per route the code serves, with the full path composed across files: an Elysia, Express or Hono chain's own prefix (new Elysia({ prefix: '/notebooks' }), .basePath('/v1')) beneath every .use(child), .use('/p', child) or .route('/p', child) that mounts it, up to the top-level chain, read through as any and as unknown as T casts and resolved through imports (aliased ones included). A chain built inline inside .use(new Elysia({ prefix }).get(…)), a .group('/v2', app => app.get(…)) or .guard() callback, and a module re-exported as export const deckModule = deckRoutes as unknown as Elysia all compose the same way. A Next.js app/api/x/[id]/route.ts exporting GET is GET /api/x/:id. A repository holding a langgraph.json with a non-empty graphs object is a LangGraph Agent Server: its 49 framework routes (POST /runs/wait, POST /threads/{thread_id}/runs/stream, GET /assistants/{assistant_id}, ..., the table @langchain/langgraph-api 1.5.1 registers, less its fo
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