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codebase-memory-mcp

by DeusData·2,363·Score 58

High-performance code intelligence MCP server that indexes codebases into a persistent knowledge graph with sub-ms queries and 155 language support.

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Overview

codebase-memory-mcp is a cutting-edge code intelligence tool that transforms codebases into structured knowledge graphs through advanced tree-sitter AST analysis. It stands out for its extreme indexing speed - able to process the Linux kernel (28M LOC, 75K files) in just 3 minutes - and offers 14 MCP tools for comprehensive code exploration. The server provides zero-dependency operation through a single static binary across multiple platforms, with built-in 3D graph visualization UI available at localhost:9749. Its research-backed approach demonstrates significant efficiency improvements, reducing token usage by 10x and tool calls by 2.1x compared to traditional file-by-file exploration methods.

Try asking AI

After installing, here are 8 things you can ask your AI assistant:

you:Large codebase architecture analysis and documentation
you:Code impact assessment before refactoring
you:Cross-service dependency mapping in microservices
you:Dead code detection and optimization
you:Semantic code search across entire repositories
you:What languages are supported?
you:How does it handle large codebases?
you:Is it secure?

When to choose this

Choose this for large codebases that need fast, structural analysis across multiple languages with local processing and minimal token usage.

When NOT to choose this

Don't choose if you need write access to the codebase, as this is a read-only indexing tool, or if you prefer cloud-based solutions.

Tools this server exposes

12 tools extracted from the README
  • get_architecture

    Returns languages, packages, entry points, routes, hotspots, boundaries, layers, and clusters

  • manage_adr

    Persists architectural decisions across sessions

  • detect_changes

    Maps uncommitted changes to affected symbols with risk classification

  • semantic_query

    Vector search across the entire graph using embedded code embeddings

  • search_graph

    Searches the graph with regex patterns, filters, and degree constraints

  • search_code

    Graph-augmented grep over indexed files only

  • trace_call_path

    Resolves function calls across files and packages

  • detect_dead_code

    Finds functions with zero callers, excluding entry points

  • index_repository

    Indexes the current repository into the knowledge graph

  • get_cross_repo_links

    Shows links between nodes across multiple indexed repositories

  • find_http_routes

    Finds HTTP routes and their implementations in the codebase

  • find_channels

    Detects pub-sub patterns across services and modules

Comparable tools

semantic-code-search-mcpcode-search-mcptree-sitter-lspsemantic-code-search

Installation

Quick Start

**One-line install** (macOS / Linux):

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

**Windows** (PowerShell):

# 1. Download the installer
Invoke-WebRequest -Uri https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.ps1 -OutFile install.ps1

# 2. (Optional but recommended) Inspect the script
notepad install.ps1

# 3. Run it
.\install.ps1
Claude Desktop Configuration
  1. Add to Claude Desktop config:
{
  "mcpServers": {
    "codebase-memory": {
      "command": "codebase-memory-mcp",
      "args": []
    }
  }
}
  1. Restart Claude Desktop
  2. Say "Index this project" to begin

FAQ

What languages are supported?
codebase-memory-mcp supports 155 programming languages through vendored tree-sitter grammars compiled into the binary. It offers enhanced LSP-style type resolution for Go, C, C++, and TypeScript/JavaScript.
How does it handle large codebases?
It uses a RAM-first pipeline with LZ4 compression and in-memory SQLite, processing the Linux kernel (28M LOC) in 3 minutes. Memory is released after indexing, and it includes auto-sync for change detection.
Is it secure?
Yes - all processing happens 100% locally with no external API calls. Every release binary is signed, checksummed, and scanned by 70+ antivirus engines. Full source code is available for audit.

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Last updated · Auto-generated from public README + GitHub signals.