Code-Graph-RAG

Name: Code-Graph-RAG
Author: vitali87

by vitali87version 0.6.30i★ 5,349iRuns on your computer

Registry nameio.github.vitali87/code-graph-rag

How to install

What it does

Knowledge-graph RAG for multi-language codebases: index, query and edit code in natural language.

Connects Runs on your computer
Account or key Needs ORCHESTRATOR_API_KEY, CYPHER_API_KEY
Category Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Passed 3/3 checks · Runs on your computer · ✓ Commands checked Nov 13, 2026

First: which AI do you use?

ClaudeWeb · app · phoneChatGPTWebClaude CodeTerminalCursorCode editorVS CodeCode editorOtherOther apps

Pick your app and the steps appear below.

Works with Claude, with some setup first

You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Code-Graph-RAG key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Code-Graph-RAG site ↗
Done
Open the Claude desktop app’s settings file
SettingsDeveloperEdit Config
Done

Paste these settings and save the file

{
  "mcpServers": {
    "code-graph-rag": {
      "command": "uvx",
      "args": [
        "code-graph-rag",
        "mcp-server"
      ],
      "env": {
        "ORCHESTRATOR_PROVIDER": "your-value",
        "ORCHESTRATOR_MODEL": "your-value",
        "ORCHESTRATOR_API_KEY": "your-value",
        "CYPHER_PROVIDER": "your-value",
        "CYPHER_MODEL": "your-value",
        "CYPHER_API_KEY": "your-value",
        "MEMGRAPH_HOST": "your-value",
        "MEMGRAPH_PORT": "your-value",
        "TARGET_REPO_PATH": "your-value"
      }
    }
  }
}

Paste the key only into the app’s field, never into a chat or to anyone

Done

Quit Claude and open it again
Done
Try it
Use Code-Graph-RAG and tell me what you can do for me, then show me one thing
✓ If Claude says it is using Code-Graph-RAG or shows a Code-Graph-RAG tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

ChatGPT cannot connect Code-Graph-RAG yet

Code-Graph-RAG runs on your computer, but ChatGPT can only connect servers that run on the web

What you can do instead

A · Use an app that can connect Code-Graph-RAG

Steps for Claude →You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
Steps for Claude Code →You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)
Steps for Cursor →You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)
Steps for VS Code →You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

B · Others in Search & AI memory that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Context7✓ ChatGPT
AIHOT✓ ChatGPT
Sui Knowledge Base (kapa.ai)✓ ChatGPT

Works with Claude Code, with some setup first

You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Code-Graph-RAG key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Code-Graph-RAG site ↗
Done
Open Terminal
Mac: press Command+Space and type Terminal · Windows: open PowerShell
Done

Paste this command and press Enter

claude mcp add --scope user code-graph-rag --env ORCHESTRATOR_PROVIDER=your-value --env ORCHESTRATOR_MODEL=your-value --env ORCHESTRATOR_API_KEY=your-value --env CYPHER_PROVIDER=your-value --env CYPHER_MODEL=your-value --env CYPHER_API_KEY=your-value --env MEMGRAPH_HOST=your-value --env MEMGRAPH_PORT=your-value --env TARGET_REPO_PATH=your-value -- uvx code-graph-rag mcp-server

Replace “your-value” with your key before pressing Enter

Paste the key only into the app’s field, never into a chat or to anyone

Done

Type /mcp in Claude Code
You should see Code-Graph-RAG listed as connected
Done
Try it
Use Code-Graph-RAG and tell me what you can do for me, then show me one thing
✓ If Claude Code says it is using Code-Graph-RAG or shows a Code-Graph-RAG tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor, with some setup first

You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Code-Graph-RAG key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Code-Graph-RAG site ↗
Done
Click this button to open Cursor
Open in Cursor
Cursor asks you to confirm; click Install
Done
Fill in your key
In the Code-Graph-RAG settings, ORCHESTRATOR_PROVIDER, ORCHESTRATOR_MODEL, ORCHESTRATOR_API_KEY, CYPHER_PROVIDER, CYPHER_MODEL, CYPHER_API_KEY, MEMGRAPH_HOST, MEMGRAPH_PORT, TARGET_REPO_PATH is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Done
Open the AI chat in Cursor in Agent mode
Done
Try it
Use Code-Graph-RAG and tell me what you can do for me, then show me one thing
✓ If Cursor says it is using Code-Graph-RAG or shows a Code-Graph-RAG tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code, with some setup first

You need a Code-Graph-RAG key (create it on the maker’s site) · Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Sign up and create a Code-Graph-RAG key
Open the maker’s site, sign up and create an API key for the next step. Check the maker’s site for pricing and free plans.
Open the Code-Graph-RAG site ↗
Done
Click this button to open VS Code
Open in VS Code
VS Code asks you to confirm; click Install
Done
Fill in your key
In the Code-Graph-RAG settings, ORCHESTRATOR_PROVIDER, ORCHESTRATOR_MODEL, ORCHESTRATOR_API_KEY, CYPHER_PROVIDER, CYPHER_MODEL, CYPHER_API_KEY, MEMGRAPH_HOST, MEMGRAPH_PORT, TARGET_REPO_PATH is empty; add your key and save
Paste the key only into the app’s field, never into a chat or to anyone
Done
Open the AI chat in VS Code in Agent mode
Done
Try it
Use Code-Graph-RAG and tell me what you can do for me, then show me one thing
✓ If VS Code says it is using Code-Graph-RAG or shows a Code-Graph-RAG tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use Code-Graph-RAG💬 Discussion →

For developers: Terminal commands and JSON settings

Installed on your computer

Claude Code

claude mcp add --scope user code-graph-rag --env ORCHESTRATOR_PROVIDER=your-value --env ORCHESTRATOR_MODEL=your-value --env ORCHESTRATOR_API_KEY=your-value --env CYPHER_PROVIDER=your-value --env CYPHER_MODEL=your-value --env CYPHER_API_KEY=your-value --env MEMGRAPH_HOST=your-value --env MEMGRAPH_PORT=your-value --env TARGET_REPO_PATH=your-value -- uvx code-graph-rag mcp-server

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "code-graph-rag": {
      "command": "uvx",
      "args": [
        "code-graph-rag",
        "mcp-server"
      ],
      "env": {
        "ORCHESTRATOR_PROVIDER": "your-value",
        "ORCHESTRATOR_MODEL": "your-value",
        "ORCHESTRATOR_API_KEY": "your-value",
        "CYPHER_PROVIDER": "your-value",
        "CYPHER_MODEL": "your-value",
        "CYPHER_API_KEY": "your-value",
        "MEMGRAPH_HOST": "your-value",
        "MEMGRAPH_PORT": "your-value",
        "TARGET_REPO_PATH": "your-value"
      }
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "code-graph-rag": {
      "command": "uvx",
      "args": [
        "code-graph-rag",
        "mcp-server"
      ],
      "env": {
        "ORCHESTRATOR_PROVIDER": "your-value",
        "ORCHESTRATOR_MODEL": "your-value",
        "ORCHESTRATOR_API_KEY": "your-value",
        "CYPHER_PROVIDER": "your-value",
        "CYPHER_MODEL": "your-value",
        "CYPHER_API_KEY": "your-value",
        "MEMGRAPH_HOST": "your-value",
        "MEMGRAPH_PORT": "your-value",
        "TARGET_REPO_PATH": "your-value"
      }
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "code-graph-rag": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "code-graph-rag",
        "mcp-server"
      ],
      "env": {
        "ORCHESTRATOR_PROVIDER": "your-value",
        "ORCHESTRATOR_MODEL": "your-value",
        "ORCHESTRATOR_API_KEY": "your-value",
        "CYPHER_PROVIDER": "your-value",
        "CYPHER_MODEL": "your-value",
        "CYPHER_API_KEY": "your-value",
        "MEMGRAPH_HOST": "your-value",
        "MEMGRAPH_PORT": "your-value",
        "TARGET_REPO_PATH": "your-value"
      }
    }
  }
}

Values you fill in

ORCHESTRATOR_PROVIDER env
LLM provider for the orchestrator agent (openai, anthropic, google, azure, cohere, ollama)
ORCHESTRATOR_MODEL env
Model name for the orchestrator agent
ORCHESTRATOR_API_KEY secret env
API key for the orchestrator LLM provider (not needed for the default local ollama provider)
CYPHER_PROVIDER env
LLM provider for Cypher query generation (openai, anthropic, google, azure, cohere, ollama)
CYPHER_MODEL env
Model name for Cypher query generation
CYPHER_API_KEY secret env
API key for the Cypher LLM provider (not needed for the default local ollama provider)
MEMGRAPH_HOST env
Hostname of the Memgraph database
MEMGRAPH_PORT env
Port of the Memgraph database
TARGET_REPO_PATH env
Path to the repository to analyze (auto-detected from working directory if not set)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

GitHub stars i: 5,349
Downloads per weeki: 869/wk
Licence i: MIT
Connection: Runs on your computer
Transport: stdio
Latest versioni: 0.6.30
Categoryi: Search & AI memory
Published to registryi: Nov 10, 2026
Code last changedi: Nov 12, 2026
Maker: vitali87
Packages: pypi: code-graph-rag
Repo: vitali87/code-graph-rag
Website: code-graph-rag.com
Registry status: Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

All apps, with pros and cons →

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 13, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account vitali87, which owns the repo
✓ Pass
Still maintained
Code last changed yesterday
✓ Pass
Has a licence
Uses MIT
– 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

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

No posts yet. Be the first to ask or share.

Posts here are written by users, not the PopNx team.

User reviews

No reviews yet

Compared with others in Search & AI memoryi

More stars than 99% of the other 6045 servers in this category
Published to the registry more recently than 90% of the other 6045 servers in this category
Basic checks equal to or better than 100% of the other 6045 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 Code-Graph-RAG safe?

It passed 3 of 3 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?

You need to fill in: ORCHESTRATOR_API_KEY, CYPHER_API_KEY

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 yesterday, and the latest version (0.6.30) reached the registry 3 days 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, Ruflo

Others in the same category

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 1.2M/wk★ 64.7KUpdated yesterday

Computer or cloud

Install

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 16.8K/wk★ 48.6KUpdated 27 days ago

Runs on your computer

Install

Ruflo

Agent teams, swarms, memory and hooks for Claude Code and Codex, served over MCP.

by ruvnetWidely used↓ 74.3K/wk★ 81.6K Stars for the whole repoUpdated today

Runs on your computer

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.

Code-Graph-RAG

Code-Graph-RAG parses a multi-language codebase with Tree-sitter, sharpened by compiler-grade frontends and runtime traces where available, builds a knowledge graph of its structure in an embedded graph database that needs no server, and lets you query, edit, and optimise that code in plain English. It works across a monorepo of mixed languages under one unified graph schema.

Index: cgr start --update-graph parses a repository into a knowledge graph (sped up)

Ask: cgr start answers questions and edits code, grounded in that graph

Latest News 🔥

Rust Upgrade: Updated Rust to version 1.99.1-slim-trixie.
Signature Functionality: Added support for reading and writing JavaScript headers for change signatures, including the ability to change the signature of JavaScript functions or methods.
macOS Compatibility: The build now leaves macOS-14 support.

See NEWS.md for the full history.

What It Does

Point Code-Graph-RAG at a repository and it reads every source file, extracts functions, classes, methods, modules, and the relationships between them, and stores the result as an interconnected graph. Once the graph exists you can:

Ask questions about the codebase in natural language and get answers grounded in the real structure.
Retrieve the actual source of any function, class, or method by name or by intent.
Edit code through the agent with AST-based surgical patching and a diff preview before anything changes.
Optimise code against language best practices or your own coding standards.
Find dead code by walking call and reference edges from entry points.
Search and rewrite structurally by AST pattern with ast-grep.
Overlay runtime behaviour: trace a test run (or pull production eBPF profiles) with cgr trace and merge the calls that actually happened into the graph, exposing dispatch that static analysis cannot see.

How It Works

The system has two components:

Multi-language parser. A Tree-sitter based parser reads the codebase and ingests functions, classes, methods, modules, and their relationships into the graph under a single language-agnostic schema. Where a toolchain is available, compiler-grade frontends layer exact facts on top (libclang for C/C++, go/types for Go, and opt-in Roslyn, javac and Jedi for C#, Java and Python), and dynamic tracing merges calls observed at runtime. Tree-sitter stays the backbone: a trace only sees code that ran, and a compiler frontend only covers what its toolchain can build.
RAG system (codebase_rag/). An interactive CLI that turns natural language into Cypher queries, retrieves matching code, and drives AI-powered editing and optimisation.

Source Code -> Tree-sitter Parser -> AST Analysis -> Knowledge Graph

| User Query -> AI Model (Cypher Gen) -> Cypher Query -> Graph Results -> Response

The graph is stored in an embedded SQLite file by default. Memgraph and Neo4j are opt-in backends that run the same Cypher; Graph Backends compares them.

See the Architecture Overview and Graph Schema for the full picture.

Supported Languages

Python, TypeScript, TSX, JavaScript, Rust, Go, Java, C, C++, C#, PHP, Lua, Dart, and Julia are fully supported. Scala is in development, and Ruby, Kotlin, Swift, Elixir, Haskell, Solidity, Bash, and Nix have structural support (modules, functions, classes where the language has them, and imports) through the pluggable ast-grep tier. See the Language Support matrix for per-language capabilities.

Installation

cgr is published to PyPI. Install it system-wide with the treesitter-full (tree-sitter grammars), ast-grep (Ruby, Kotlin, Swift, Elixir, Haskell, Solidity, Bash, Nix) and semantic (vector search) extras:

# with uv (recommended)

uv tool install "code-graph-rag[treesitter-full,ast-grep,semantic]"

or with pipx

pipx install "code-graph-rag[treesitter-full,ast-grep,semantic]"

Which version am I getting?

Three version lines exist and they intentionally differ:

where	what it tracks
git tags	every version, one per merge
GitHub Releases (binaries, signatures)	every 50th version, plus any security fix, breaking change or merge labelled `release now`
PyPI	every 50th version, plus any security fix, breaking change or merge labelled `release now`

So the newest tag on main usually runs ahead of the newest release, often by tens of patch versions; they coincide only just after a release. Nothing is stuck, the cadences differ by design. A security fix, a breaking change or a merge a maintainer labels release now does NOT wait for the cadence: each ships a release and a PyPI upload immediately.

uv tool install and pipx install give you the newest PyPI version, which is the newest RELEASE, not the newest tag. Interim tags exist so every merge is addressable; binaries and PyPI uploads follow the cadence above.

To run code newer than the latest release, install from git:

uv tool install "code-graph-rag[treesitter-full,ast-grep,semantic] @ git+https://github.com/vitali87/code-graph-rag@main"

To upgrade an existing install, run uv tool upgrade code-graph-rag (with pipx, pipx upgrade code-graph-rag, or pipx reinstall code-graph-rag for a git install). Upgrade covers the other install methods.

You also need Python 3.12+ and ripgrep. The graph lives in an embedded SQLite file by default, so there is no database server to run: no Docker and no cmake. Memgraph and Neo4j remain available as opt-in backends (Graph Backends). Full prerequisites, source installs, and environment setup are in the Installation guide.

[!NOTE]

The wheel is pure Python (py3-none-any), so it installs on any platform with Python 3.12 or newer. Older system interpreters (Debian Bookworm ships 3.11) need the interpreter pinned explicitly; see Installation for the commands.

Quick Start

# Parse a repository into the graph, then query it

cgr start --repo-path /path/to/repo --update-graph cgr start --repo-path /path/to/repo

The graph is written to ~/.cgr/graph.sqlite (set SQLITE_GRAPH_PATH to move it). To use Memgraph instead, install the driver with the memgraph extra, set GRAPH_BACKEND=memgraph, and start the packaged Memgraph + Qdrant stack with cgr daemon up.

Repeat the first command for each repository you want indexed; the graph is shared, and syncing one project leaves the others alone. To start over from an empty graph, add --clean — it deletes every project in the shared graph, not just this one, and asks for confirmation first when other projects would be destroyed.

A default index leaves out the opt-in capture groups; add them with --capture or CGR_CAPTURE.

The Quick Start guide walks through parsing, querying, and exporting in five minutes.

MCP Server

Code-Graph-RAG runs as an MCP server so Claude Code and other MCP clients can query and edit your codebase directly. See the MCP Server guide for setup.

Documentation

Getting Started

User Guide

Architecture

Python SDK

Advanced

Enterprise Services

Code-Graph-RAG is open source and free to use. For organisations that need more, we offer fully managed cloud-hosted solutions and on-premise deployments:

Only the beginning is shown; read the rest in the repo

Code-Graph-RAG

What it does

Install

Install Python (uv)

Sign up and create a Code-Graph-RAG key

Open the Claude desktop app’s settings file

Paste these settings and save the file

Quit Claude and open it again

Try it

What you can do instead

Install Python (uv)

Sign up and create a Code-Graph-RAG key

Open Terminal

Paste this command and press Enter

Type /mcp in Claude Code

Try it

Install Python (uv)

Sign up and create a Code-Graph-RAG key

Click this button to open Cursor

Fill in your key

Open the AI chat in Cursor in Agent mode

Try it

Install Python (uv)

Sign up and create a Code-Graph-RAG key

Click this button to open VS Code

Fill in your key

Open the AI chat in VS Code in Agent mode

Try it

Installed on your computer

Values you fill in

At a glance

Which apps can use it

Related guides

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Discussion

User reviews

Compared with others in Search & AI memoryi

Common questions

Others in the same category

Context7

Codebase Memory

Ruflo

README from the maker

Code-Graph-RAG

Latest News 🔥

What It Does

How It Works

Supported Languages

Installation

or with pipx

Which version am I getting?

Quick Start

MCP Server

Documentation

Enterprise Services