Files
codebase-memory-mcp/pkg/npm
Martin Vogel 331a581551 docs(post-release): align README, server.json, package wrappers with v0.6.1
- README badges: languages 66->155, agents 10->11, tests 2586->2812 (actual count from v0.6.1 test run)
- README: VirusTotal table, primary VT badge link, all '66 languages' references, expanded language list with all newly added grammars
- server.json: bump 0.5.5->0.6.1 (was two releases behind), update all download URLs and sha256s
- pkg/scoop, homebrew, aur, chocolatey, winget: bump to 0.6.1 with new sha256s from v0.6.1 checksums.txt
- pkg/winget: new 0.6.1/ manifest directory (winget keeps version history; 0.6.0/ retained)
- pkg/npm/README: language and agent counts
2026-05-05 00:44:35 +02:00
..

codebase-memory-mcp

npm GitHub Release License Platform

The fastest and most efficient code intelligence engine for AI coding agents. Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a single static binary — this package downloads and runs it automatically.

High-quality parsing through tree-sitter AST analysis across 155 languages — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 11 coding agents.

Installation

npm install -g codebase-memory-mcp

The binary for your platform is downloaded automatically at install time. Then configure your coding agents:

codebase-memory-mcp install

Restart your agent. Say "Index this project" — done.

Why codebase-memory-mcp

  • Extreme indexing speed — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline with LZ4 compression and in-memory SQLite.
  • Plug and play — single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys.
  • 155 languages — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.
  • 120x fewer tokens — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search.
  • 11 agents, one command — install auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, OpenClaw, and Kiro.
  • 14 MCP tools — search, trace, architecture, impact analysis, Cypher queries, dead code detection, cross-service HTTP linking, ADR management, and more.

Supported Platforms

OS Architecture
macOS arm64, amd64
Linux arm64, amd64
Windows amd64

Usage

codebase-memory-mcp install          # configure all detected coding agents
codebase-memory-mcp --version
codebase-memory-mcp --help
codebase-memory-mcp update           # update to latest release
codebase-memory-mcp uninstall        # remove agent configs

CLI Mode

Every MCP tool is also available directly from the command line:

codebase-memory-mcp cli index_repository '{"repo_path": "/path/to/repo"}'
codebase-memory-mcp cli search_graph '{"name_pattern": ".*Handler.*", "label": "Function"}'
codebase-memory-mcp cli trace_call_path '{"function_name": "main", "direction": "both"}'
codebase-memory-mcp cli get_architecture '{}'

MCP Tools

Category Tools
Indexing index_repository, list_projects, delete_project, index_status
Querying search_graph, trace_call_path, detect_changes, query_graph
Analysis get_architecture, get_graph_schema, get_code_snippet, search_code
Advanced manage_adr, ingest_traces

Performance

Benchmarked on Apple M3 Pro:

Operation Time
Linux kernel full index (28M LOC, 75K files) 3 min
Django full index ~6s
Cypher query <1ms
Trace call path (depth=5) <10ms

Full Documentation

See github.com/DeusData/codebase-memory-mcp for the full README including all MCP tools, configuration options, graph data model, and language support details.

License

MIT