deepset-mcp 0.1.7

Collection of MCP tools and Agents to work with the deepset AI platform. Create, debug or learn about pipelines on the platform. Useable from the CLI, Cursor, Claude Code, or other MCP clients.

deepset-mcp

The official MCP server and Python SDK for the deepset AI platform

deepset-mcp enables AI agents to build and debug pipelines on the Haystack Enterprise AI platform through 30+ specialized tools. It also provides a Python SDK for programmatic access to many platform resources.

Documentation

📖 View the full documentation

Quick Links

• 🔗 Haystack Enterprise AI platform
• 📚 Installation Guide
• 🛠️ MCP Server Guide
• 🐍 Python SDK Guide

Development

Installation

Install the project using uv:

# Install uv first
pipx install uv

# Install project with all dependencies
uv sync --locked --all-extras --all-groups

Local Development

If you want to test your changes locally, follow these steps:

1. Add a script run-deepset-mcp.sh that uses the binary from the project's virtual env

#!/usr/bin/env bash
# Wrapper to run the local deepset-mcp server for Cursor MCP.
# Use this as command so it doesn't depend on uv or PATH.
set -e
cd "$(dirname "$0")"
exec .venv/bin/deepset-mcp

2. Use it this way in Cursor:

    "deepset": {
      "command": "/bin/bash",
      "args": ["/Users/*****/****/deepset-mcp-server/run-deepset-mcp.sh"],
      "cwd": "/Users/*****/****/deepset-mcp-server",
      "env": {
        "DEEPSET_WORKSPACE": "WORKSPACE",
        "DEEPSET_API_KEY": "API_KEY"
      }
    }

Note: If you change the codebase, make sure to restart the MCP server.

Code Quality & Testing

Run code quality checks and tests using the Makefile:

# Install dependencies
make install

# Code quality
make lint          # Run ruff linting
make format        # Format code with ruff
make types         # Run mypy type checking

# Testing
make test          # Run unit tests (default)
make test-unit     # Run unit tests only
make test-integration     # Run integration tests
make test-all      # Run all tests

# Clean up
make clean         # Remove cache files

Documentation

Documentation is built using MkDocs with the Material theme:

• Configuration: mkdocs.yml
• Content: docs/ directory
• Auto-generated API docs via mkdocstrings
• Deployed via GitHub Pages (automated via GitHub Actions on push to main branch)