Cowork History MCP

An MCP (Model Context Protocol) server for searching and browsing your Claude conversation history stored in ~/.claude/. Works with both Claude Code and Cowork conversations.

Features

• Hybrid Search - Combines multiple search methods for best results:
  • SQLite FTS5 - Fast full-text search with BM25 ranking
  • macOS Spotlight - Leverages system content indexing via mdfind
  • Vector Embeddings - Semantic similarity search (optional, requires Ollama)
• Smart Path Reconstruction - Recovers actual filesystem paths via probing (not heuristic guessing)
• Persistent Index - SQLite database with incremental updates for fast queries
• Ollama Setup Tools - Automated installation and configuration for embeddings

Installation

Option 1: Claude Desktop (One-Click Install)

Download cowork-history.mcpb from the latest release and double-click to install.

Option 2: Via uvx (Recommended for CLI)

uvx cowork-history

Option 3: Via pip

pip install cowork-history

Option 4: Manual Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "cowork-history": {
      "command": "uvx",
      "args": ["cowork-history"],
      "env": {
        "OLLAMA_URL": "http://localhost:11434",
        "EMBEDDING_MODEL": "nomic-embed-text"
      }
    }
  }
}

Quick Start

Once installed, Claude can search your conversation history:

"What did we discuss about authentication last week?"
"Find the conversation where we debugged the payment webhook"
"Show me my conversations in the my-project folder"

Available Tools

Search & Browse

Tool	Description
cowork_history_search	Search conversations using hybrid search (FTS + Spotlight + vector)
cowork_history_list	List recent conversations, optionally filtered by project
cowork_history_get	Get full content of a specific conversation by session ID
cowork_history_projects	List all projects with conversation history
cowork_history_stats	Get statistics and search capability status
cowork_history_reindex	Rebuild index and optionally generate embeddings

Ollama Setup (for Vector Search)

Tool	Description
history_system_check	Check system requirements for Ollama
history_setup_ollama	Install Ollama via Homebrew (macOS)
history_setup_ollama_direct	Install Ollama via direct download (no Homebrew)
history_ollama_status	Check Ollama status and embedding model availability

Search Modes

The cowork_history_search tool supports multiple search modes:

Mode	Description
auto (default)	Uses all available methods, best results
fts	Full-text search only (fastest)
spotlight	macOS Spotlight only
vector	Semantic similarity only (requires Ollama)
hybrid	Explicit combination with ranking

Search Examples

"authentication bug"           → finds conversations with both words
"how to deploy"                → semantic search finds related discussions
"\"exact phrase\""             → exact phrase matching
project:"my-app" "database"    → filter by project

Enabling Vector Search

Vector search provides semantic similarity matching (finding related concepts even without exact keywords). It requires Ollama with an embedding model.

Quick Setup

Ask Claude to set it up for you:

"Set up Ollama for vector search"

Or manually:

# Install Ollama (macOS)
brew install ollama

# Start Ollama service
brew services start ollama

# Pull the embedding model
ollama pull nomic-embed-text

Then generate embeddings:

"Rebuild the history index with embeddings"

How It Works

Indexing

The server maintains a SQLite database at ~/.claude/.history-index/conversations.db with:

• FTS5 virtual table for fast full-text search
• Conversation metadata (session ID, project, timestamps, topic)
• Full content for comprehensive search
• Path cache for reconstructed paths
• Embeddings table for vector search (optional)

The index updates automatically when you search (if >5 minutes old) or you can force a rebuild with cowork_history_reindex.

Environment Variables

Variable	Default	Description
OLLAMA_URL	http://localhost:11434	Ollama server URL
EMBEDDING_MODEL	nomic-embed-text	Ollama embedding model

Troubleshooting

No conversations found

1. Make sure ~/.claude/ directory exists
2. Check that you have conversation history (use Claude Code or Cowork first)
3. Verify the MCP server is properly configured

Vector search not available

1. Check Ollama is installed: ollama --version
2. Check Ollama is running: curl http://localhost:11434/api/tags
3. Check model is available: ollama list
4. Pull embedding model: ollama pull nomic-embed-text

Search not finding expected results

• Try natural language queries (semantic search is more flexible)
• Use mode: "fts" for exact phrase matching
• Check cowork_history_stats to see which search backends are active

Development

Running locally

# Clone the repository
git clone https://github.com/egoughnour/cowork-history
cd cowork-history

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest tests/

# Run the server directly
python -m src.cowork_history_server

Testing with MCP Inspector

npx @modelcontextprotocol/inspector uvx cowork-history

License

MIT License - see LICENSE file for details.