feyod-mcp vs fetch

Side-by-side comparison to help you pick between these two MCP servers.

	feyod-mcp by jeroenvdmeer	fetch by modelcontextprotocol
Stars	★ 1	★ 85,748
30d uses	—	—
Score	31	76
Official	—	✓
Categories	AI / LLM ToolsDatabaseOther	Web ScrapingAI / LLM ToolsProductivity
Language	Python	TypeScript
Last commit	10 mo ago	this month

feyod-mcp · Summary

MCP server for Feyenoord football data queries via natural language interface.

fetch · Summary

An MCP server that fetches web content and converts HTML to markdown, allowing LLMs to read web pages.

feyod-mcp · Use cases

Querying Feyenoord match results, lineups, and player statistics
Finding information about specific players and their performance
Retrieving historical data about opponents and past matches

fetch · Use cases

LLMs reading news articles and blogs
Content analysis of web pages
Retrieving information from public websites
Chunked reading of large web documents

feyod-mcp · Install

Installation

Using Docker (Recommended)

# Pull the Docker image
docker pull jeroenvdmeer/feyod-mcp

# Run the container
docker run -p 8000:8000 \
  -e LLM_PROVIDER="google" \
  -e LLM_API_KEY="your_api_key" \
  jeroenvdmeer/feyod-mcp

Local Setup

# Clone repositories
git clone https://github.com/jeroenvdmeer/feyod-mcp.git
git clone https://github.com/jeroenvdmeer/feyod.git
cd feyod-mcp

# Create and activate virtual environment
uv venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows

# Install dependencies
uv add "mcp[cli]" langchain langchain-openai langchain-google-genai python-dotenv aiosqlite

# Set up database
cd ../feyod
sqlite3 feyod.db < feyod.sql

cd ../mcp

Claude Desktop Configuration

Add to Claude Desktop config.json:

{
  "mcpServers": {
    "feyod": {
      "command": "python",
      "args": ["/path/to/feyod-mcp/main.py"],
      "env": {
        "LLM_PROVIDER": "google",
        "LLM_API_KEY": "your_api_key",
        "DATABASE_PATH": "../feyod/feyod.db"
      }
    }
  }
}

fetch · Install

Installation

**Using uv (recommended)** No specific installation needed. Use uvx to run the server directly:

uvx mcp-server-fetch

**Using PIP** Install via pip:

pip install mcp-server-fetch

Then run as:

python -m mcp_server_fetch

Claude Desktop Configuration

{
  "mcpServers": {
    "fetch": {
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    }
  }
}

Comparison generated from public README + GitHub signals. Last updated automatically.