LibreAI / KI-Agenten / codebase-memory-mcp

// agents · DeusData/codebase-memory-mcp

codebase-memory-mcp

codebase-memory-mcp ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von DeusData (DeusData/codebase-memory-mcp auf GitHub). Es hat 46.150 Sterne auf GitHub und 3.796 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 7. Oktober 2026 auf GitHub aktualisiert.

High-performance code intelligence MCP server: your codebase as a persistent knowledge graph

★ 46,1 Tsd. Sterne⑂ 3,8 Tsd. ForksMITaktualisiert Okt 2026

Auf GitHub ansehen ↗Official site ↗

▦ Visual — das README dieses Projekts enthält keinen einbettbaren Screenshot,
darum hier ein Platzhalter. Die Anleitung unten ist trotzdem vollständig.

// projektdaten

Projektdaten

Repository: DeusData/codebase-memory-mcp
GitHub-Sterne: 46.150
Forks: 3.796
Lizenz: MIT
Zuletzt auf GitHub aktualisiert: 7. Oktober 2026
Kategorie: KI-Agenten
Eintragstyp: Vollständige Installationsanleitung
Offizielle Website: Official site

// so funktioniert es

So funktioniert es

Clarify your goal
Decide what you want from codebase-memory-mcp and check the README and requirements to confirm it fits your setup and C environment.
Get the code
Clone the repository from GitHub (github.com/DeusData/codebase-memory-mcp) or use the documented install channel if you do not need the source.
Install and configure
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Run your first task
Work through the README's first example end to end, then adapt it to your own project or data.

// funktionen

Warum es so beliebt ist

Persistent code graph

Indexes codebases into a persistent knowledge graph stored in SQLite.

158 languages

Supports 158 programming languages through tree-sitter based parsing.

Single static binary

One static binary with zero dependencies — install is a single script.

Sub-millisecond queries

Graph queries answer in sub-millisecond times, per the project description.

Token savings

Designed to answer code questions with far fewer tokens than reading raw files.

Graph visualization UI

Includes a graph visualization UI and an auto-indexing session daemon.

// selbst ausführen

Führe es selbst aus

Clone the repository

Start by getting the source and entering the project directory.

git clone https://github.com/DeusData/codebase-memory-mcp.git
cd codebase-memory-mcp

Run the installer

The README's quick start installs the binary with one curl command.

curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash

Index your repo and connect
Let it auto-index your codebase, then connect it as an MCP server to Claude Code, Cursor or Codex.
```
# see README for the exact command — Quick Start
```

// anwendungsfälle

Was du damit bauen kannst

Answering architecture questions about a huge monorepo
Letting an agent find callers and dependencies without reading thousands of files
Cross-repository code intelligence for a platform team
Visualizing a codebase's structure for onboarding

// häufige fragen

Häufige Fragen

Who maintains codebase-memory-mcp?

It is maintained by DeusData and contributors on GitHub, where the repository github.com/DeusData/codebase-memory-mcp is the canonical home for code, issues and releases.

Is codebase-memory-mcp free to use?

Yes — it is open source under the MIT license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.

Does it need a paid API key?

No. It runs fully locally as a binary; your agent keeps using your own account.

How does codebase-memory-mcp compare to alternatives?

Compared with grep and manual exploration: This server pre-indexes a queryable graph, so agents get structural answers in milliseconds instead of scanning files.

How do I get started?

Clone github.com/DeusData/codebase-memory-mcp, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.

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Hol dir codebase-memory-mcp

Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.

Auf GitHub ansehen ↗← Mehr Tools: KI-Agenten