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Cowork History logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 7:48:06 PM

Cowork History

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).

Hybrid search for Cowork history: FTS, Spotlight, and semantic vectors

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "cowork-history": {
      "command": "uvx",
      "args": [
        "cowork-history"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

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)

bash
uvx cowork-history

Option 3: Via pip

Terminal
pip install cowork-history

Option 4: Manual Configuration

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

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:

Code
"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

ToolDescription
cowork_history_searchSearch conversations using hybrid search (FTS + Spotlight + vector)
cowork_history_listList recent conversations, optionally filtered by project
cowork_history_getGet full content of a specific conversation by session ID
cowork_history_projectsList all projects with conversation history
cowork_history_statsGet statistics and search capability status
cowork_history_reindexRebuild index and optionally generate embeddings

Ollama Setup (for Vector Search)

ToolDescription
history_system_checkCheck system requirements for Ollama
history_setup_ollamaInstall Ollama via Homebrew (macOS)
history_setup_ollama_directInstall Ollama via direct download (no Homebrew)
history_ollama_statusCheck Ollama status and embedding model availability

Search Modes

The cowork_history_search tool supports multiple search modes:

ModeDescription
auto (default)Uses all available methods, best results
ftsFull-text search only (fastest)
spotlightmacOS Spotlight only
vectorSemantic similarity only (requires Ollama)
hybridExplicit combination with ranking

Search Examples

Code
"authentication bug"           β†’ finds conversations with both words
"how to deploy"                β†’ semantic search finds related discussions
"\"exact phrase\""             β†’ exact phrase matching
project:"my-app" "database"    β†’ 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:

Code
"Set up Ollama for vector search"

Or manually:

bash
# 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:

Code
"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

VariableDefaultDescription
OLLAMA_URLhttp://localhost:11434Ollama server URL
EMBEDDING_MODELnomic-embed-textOllama 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

bash
# 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

Terminal
npx @modelcontextprotocol/inspector uvx cowork-history

License

MIT License - see LICENSE file for details.

Read the full README β†’View source on GitHub β†’

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Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Cowork History

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "cowork-history": { "command": "uvx", "args": ["cowork-history"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedSep 7, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
35Quality signal: Fair Β· 35/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 23h ago via OSV.dev Β· cowork-history (PyPI)

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