Testing Farm MCP Server

Testing Farm MCP Server

Enables submitting FMF-based test requests to Testing Farm and listing available OS composes for testing.

Category
Visit Server

README

Testing Farm MCP Server

An MCP (Model Context Protocol) server for interacting with the Testing Farm service. This server provides tools to submit FMF-based test requests and list available composes for testing.

Container Build Static Analysis

Features

  • Submit Test Requests: Submit test requests to Testing Farm
  • List Composes: Retrieve available OS composes for testing from public or redhat ranches
  • Full Type Safety: Built with static typing
  • Async Support: Fully asynchronous API client using httpx
  • Container Ready: Container images available

Installation

Option 1: Container (Recommended)

# Pull the latest container image
podman pull ghcr.io/thrix/testing-farm-mcp:latest

# Run the MCP server
podman run -i --rm -e TESTING_FARM_API_TOKEN="your-api-token-here" ghcr.io/thrix/testing-farm-mcp:latest

This will run the MCP server with the stdio transport.

If you wanna run it via HTTP using the sse transport, you can change the default container command:

podman run -i --rm -e TESTING_FARM_API_TOKEN="your-api-token-here" -p 9001:9001 ghcr.io/thrix/testing-farm-mcp:latest \
  fastmcp run --transport sse --host 0.0.0.0 --port 9001 testing_farm_mcp/server.py

This will run the MCP server on port 9001 inside the container and it will be exposed out of the container.

Option 2: Local Development

This project uses uv for package management.

# Clone the repository
git clone https://github.com/thrix/testing-farm-mcp.git
cd testing-farm-mcp

# Install dependencies
just install

Option 3: Using ToolHive

# Using ToolHive from Stacklok
systemctl start --user podman.socket
thv secret set TESTING_FARM_API_TOKEN
thv run ghcr.io/thrix/testing-farm-mcp:latest

Configuration

Set the Testing Farm API token as an environment variable:

export TESTING_FARM_API_TOKEN="your-api-token-here"

Usage

Running the MCP Server

just start

Available Tools

submit_request

Submit a FMF test request to Testing Farm.

Parameters:

  • url (required): Git repository URL containing FMF metadata
  • ref (optional): Branch, tag, or commit to test
  • merge_sha (optional): Target commit SHA for merge testing
  • path (optional): Path to metadata tree root
  • plan_name (optional): Specific test plan to execute
  • plan_filter (optional): Filter for tmt plans
  • test_name (optional): Specific test to execute
  • test_filter (optional): Filter for tmt tests
  • environments (optional): Test environment configurations
  • notification (optional): Notification settings
  • settings (optional): Additional request settings
  • user (optional): User information

Example:

{
  "url": "https://github.com/example/test-repo",
  "ref": "main",
  "path": "/tests",
  "environments": [
    {
      "arch": "x86_64",
      "os": "fedora-38",
      "variables": {
        "TEST_VAR": "test_value"
      }
    }
  ]
}

list_composes

List available composes for a ranch.

Parameters:

  • ranch (required): Ranch to query ("redhat" or "public")

Example:

{
  "ranch": "public"
}

get_request

Get details about a Testing Farm request.

Parameters:

  • request_id (required): Testing Farm request ID or a string containing the ID, like an API request URL or artifacts URL

Example:

{
  "request_id": "12345678-1234-5678-9abc-123456789abc"
}

Container Images

Container images are available on GitHub Container Registry:

  • ghcr.io/thrix/testing-farm-mcp:latest - Latest stable version

Supported architectures:

  • linux/amd64

Development

Setup Development Environment

# Install development dependencies
just install

Code Quality

This project uses several tools for code quality:

  • ruff: Linting and formatting
  • codespell: Spell checking
  • mypy: Type checking (excluding tests)
  • pre-commit: Git hook management
just static-analysis

Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Run tests and linting
  5. Submit a pull request

Make sure to follow the existing code style and add tests for new functionality.

License

Apache-2.0 License - see LICENSE file for details.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured