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BetaBots-LLC/callimachus

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One local, searchable index of your AI coding-agent history Claude Code, Codex, Cursor, Gemini & more. Keyword + semantic search, MCP server, CLI & VS Code extension.

B

MCP

BetaBots-LLC/callimachus

Added 19 June 2026

#ai-agents #ai-tools #claude-code #codex #cursor #developer-tools #embeddings #gemini

Overview

Callimachus indexes your AI coding agent history (Claude Code, Codex, Cursor, Gemini, and more) into a single local searchable database. It supports keyword and semantic search, and provides access via a CLI, VS Code extension, and an MCP server.

Best for

Best for
Developers who use multiple AI coding assistants and want a unified, searchable record of their interactions

Use cases

  • Search past AI coding sessions by keyword or meaning
  • Integrate with MCP-compatible tools for agentic workflows
  • Browse coding history from multiple AI assistants in one place

How to use

Install

claude mcp add callimachus -- npx -y callimachus-mcp    # or any MCP client

Tools exposed

  • callimachus-mcp
  • cal

Tested with

Claude Code, Codex, Cursor, Gemini CLI, Qwen Code, Goose, OpenCode, Continue

Notes

Callimachus indexes your AI coding agent history (Claude Code, Codex, Cursor, Gemini, and more) into a single local searchable database. It supports keyword and semantic search, and provides access via a CLI, VS Code extension, and an MCP server.

5 stars on GitHub. Last updated 2026-06-19. Licensed AGPL-3.0.

Use cases

  • Search past AI coding sessions by keyword or meaning
  • Integrate with MCP-compatible tools for agentic workflows
  • Browse coding history from multiple AI assistants in one place

Pros

  • Local indexing keeps history private and offline
  • Supports multiple popular AI coding agents in one index
  • Multiple interfaces: CLI, VS Code, and MCP server

Cons

  • Index size grows with history, potentially consuming significant local storage
  • Only works with supported agents; custom agents not covered
  • Requires agents to log history; no retroactive import

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Local indexing keeps history private and offline
  • Supports multiple popular AI coding agents in one index
  • Multiple interfaces: CLI, VS Code, and MCP server

Cons

  • Index size grows with history, potentially consuming significant local storage
  • Only works with supported agents; custom agents not covered
  • Requires agents to log history; no retroactive import
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