NFL Transactions MCP

A Modular Command-line Program (MCP) for scraping NFL transaction data from ProSportsTransactions.com.

Features

Fetch NFL transactions with flexible filtering options:
- Player/Coach/Executive movement (trades, free agent signings, draft picks, etc.)
- Movements to/from injured reserve
- Movements to and from minor leagues (NFL Europe)
- Missed games due to injuries
- Missed games due to personal reasons
- Disciplinary actions (suspensions, fines, etc.)
- Legal/Criminal incidents
Filter by team, player, date range, and transaction type
Output data in CSV, JSON, or DataFrame format
List all NFL teams and transaction types

Installation

# Clone the repository git clone <repository-url> cd nfl_transactions_mcp # Install requirements pip install -r requirements.txt

Usage with Cursor

To use this MCP with Cursor, add the following configuration to your .cursor/mcp.json file:

{ "mcpServers": { "nfl-transactions": { "command": "python server.py", "env": {} } } }

Running the MCP Directly

# Run the MCP server via Cursor cursor run-mcp nfl-transactions

Available Tools

1. fetch_transactions

Fetches NFL transactions based on specified filters.

Parameters:

start_date (required): Start date in YYYY-MM-DD format
end_date (required): End date in YYYY-MM-DD format
transaction_type (optional, default: "All"): Type of transaction to filter
team (optional): Team name
player (optional): Player name
output_format (optional, default: "json"): Output format (csv, json, or dataframe)

Example:

{ "jsonrpc": "2.0", "method": "fetch_transactions", "params": { "start_date": "2023-01-01", "end_date": "2023-12-31", "transaction_type": "Injury", "team": "Patriots" }, "id": 1 }

2. list_teams

Lists all NFL teams available for filtering.

Example:

{ "jsonrpc": "2.0", "method": "list_teams", "id": 2 }

3. list_transaction_types

Lists all transaction types available for filtering.

Example:

{ "jsonrpc": "2.0", "method": "list_transaction_types", "id": 3 }

Integration with Super Agents

This MCP is designed to be easily integrated with AI agents or super agents. An agent can make JSON-RPC requests to interact with this MCP and retrieve NFL transaction data based on user queries.

Example agent integration:

# Example of an agent calling the MCP import json import subprocess def call_mcp(method, params=None): request = { "jsonrpc": "2.0", "method": method, "params": params or {}, "id": 1 } # Call the MCP via cursor cmd = ["cursor", "run-mcp", "nfl-transactions"] proc = subprocess.Popen(cmd, stdin=subprocess.PIPE, stdout=subprocess.PIPE, text=True) # Send the request and get the response response, _ = proc.communicate(json.dumps(request)) return json.loads(response) # Example: Get Patriots injury transactions from 2023 result = call_mcp("fetch_transactions", { "start_date": "2023-01-01", "end_date": "2023-12-31", "transaction_type": "Injury", "team": "Patriots" }) print(f"Found {len(result['data'])} transactions")