Fused MCP Agents

Official

local-only server

The server can only run on the client’s local machine because it depends on local resources.

Integrations

  • Allows passing any Python code directly to Claude, enabling execution of custom Python functions through the MCP server

  • Provides integration with QGIS as indicated in the MCP server configuration examples

Fused MCP Agents: Setting up MCP Servers for Data Scientists

MCP servers allow Claude & other LLMs to make HTTP requests, connecting them to APIs & executable code. We built this repo for ourselves & other data scientists to easily pass any Python code directly to your own desktop Claude app.

This repo offers a simple step-by-step notebook workflow to setup MCP Servers with Claude's Desktop App, all in Python built on top of Fused User Defined Functions (UDFs).

Requirements

If you're on Linux, the desktop app isn't available so we've made a simple client you can use to have it running locally too!

You do not need a Fused account to do any of this! All of this will be running on your local machine.

Installation

  • Clone this repo in any local directory, and navigate to the repo:
    git clone https://github.com/fusedio/fused-mcp.git cd fused-mcp/
  • Install uv if you don't have it:Macos / Linux:
    curl -LsSf https://astral.sh/uv/install.sh | sh
    Windows:
    powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
  • Test out the client by asking for its info:
    uv run main.py -h
  • Start by following our getting-started notebook fused_mcp_agents.ipynb in your favorite local IDE to get set up and then make your way to the more advanced notebook to make your own Agents & functions

Repository structure

This repo is build on top of MCP Server & Fused UDFs which are Python functions that can be run from anywhere.

Support & Community

Feel free to join our Discord server if you want some help getting unblocked!

Here are a few common steps to debug the setup:

  • Running uv run main.py -h should return something like this:

  • You might need to pass global paths to some functions to the Claude_Desktop_Config.json. For example, by default we only pass uv:
{ "mcpServers": { "qgis": { "command": "uv", "args": ["..."] } } }

But you might need to pass the full path to uv, which you can simply pass to common.generate_local_mcp_config in the notebook:

# in fused_mcp_agents.ipynb import shutil common.generate_local_mcp_config( config_path=PATH_TO_CLAUDE_CONFIG, agents_list = ["get_current_time"], repo_path= WORKING_DIR, uv_path=shutil.which('uv'), )

Which would create a config like this:

{ "mcpServers": { "qgis": { "command": "/Users/<YOUR_USERNAME>/.local/bin/uv", "args": ["..."] } } }

Contribute

Feel free to open PRs to add your own UDFs to udfs/ so others can play around with them locally too!

Using a local Claude client (without Claude Desktop app)

If you are unable to install the Claude Desktop app (e.g., on Linux), we provide a small example local client interface to use Claude with the MCP server configured in this repo:

NOTE: You'll need an API key for Claude here as you won't use the Desktop App

  • Create an Anthropic Console Account
  • Create an Anthropic API Key
  • Create a .env:
    touch .env
  • Add your key as ANTHROPIC_API_KEY inside the .env:
    # .env ANTHROPIC_API_KEY = "your-key-here"
  • Start the MCP server:
    uv run main.py --agent get_current_time
  • In another terminal session, start the local client, pointing to the address of the server:
    uv run client.py http://localhost:8080/sse
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security - not tested
A
license - permissive license
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quality - not tested

A Python-based MCP server that allows Claude and other LLMs to execute arbitrary Python code directly through your desktop Claude app, enabling data scientists to connect LLMs to APIs and executable code.

  1. Requirements
    1. Installation
      1. Repository structure
        1. Support & Community
          1. Contribute
            1. Using a local Claude client (without Claude Desktop app)