MCP SFD - Seattle Fire Department MCP Server

A Model Context Protocol (MCP) server that provides tools for LLMs to fetch and analyze Seattle Fire Department live incident data.

Features

• Low-level API proxy (sfd.fetch_raw) with normalization and caching

• Latest incident retrieval (sfd.latest_incident) for quick updates

• Fire detection (sfd.is_fire_active) with intelligent status analysis

• Evacuation monitoring (sfd.has_evacuation_orders) with keyword scanning

• Robust error handling and retry logic

• Comprehensive data normalization

• In-memory caching with configurable TTL

Related MCP server: SF Permits MCP Server

Installation

# Install the package
pip install -e .

# Install development dependencies
pip install -e ".[dev]"

Usage

Running the MCP Server

# Run with default settings
python -m mcp_sfd.server

# Or use the CLI command
mcp-sfd

Environment Variables

• SFD_BASE_URL: Base URL for SFD API (default: https://sfdlive.com/api/data/)

• DEFAULT_CACHE_TTL: Default cache TTL in seconds (default: 15)

Available Tools

sfd.fetch_raw

Low-level proxy for the SFD API with full parameter control.

{
  "order": "new",
  "length": 100,
  "search": "Any",
  "cacheTtlSeconds": 15
}

sfd.latest_incident

Returns the single most recent incident.

{}

sfd.is_fire_active

Checks if there are any active fire incidents in Seattle.

{
  "lookbackMinutes": 120
}

sfd.has_evacuation_orders

Scans for evacuation-related keywords in recent incidents.

{
  "lookbackMinutes": 180
}

Development

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=mcp_sfd

# Run specific test file
pytest tests/test_normalize.py

Code Quality

# Format code
black mcp_sfd/ tests/

# Lint
ruff check mcp_sfd/ tests/

# Type check
mypy mcp_sfd/

Architecture

The server is built with several key components:

• HTTP Client (http_client.py): Handles API requests with retry logic and caching

• Data Normalization (normalize.py): Converts upstream API format to standardized schemas

• Pydantic Schemas (schemas.py): Type-safe data models for all inputs and outputs

• Tool Implementations (tools/): Individual MCP tool logic

• Server (server.py): MCP server registration and error handling

Data Normalization

The server handles complex data transformations:

• Flattens nested upstream data structures

• Converts Seattle local time to UTC

• Normalizes coordinates from various formats

• Parses unit identifiers and status information

• Standardizes boolean fields

Error Handling

All tools use standardized MCP error codes:

• UPSTREAM_HTTP_ERROR: API connectivity issues

• UPSTREAM_TIMEOUT: Request timeouts

• SCHEMA_VALIDATION_ERROR: Data parsing failures

License

MIT