FEMA MCP Server for Pydantic AI 11 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect FEMA through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to FEMA "
"(11 tools)."
),
)
result = await agent.run(
"What tools are available in FEMA?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About FEMA MCP Server
Connect to the OpenFEMA public database through any AI agent and gain instant access to official data regarding disasters, emergency management, and federal assistance programs.
Pydantic AI validates every FEMA tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
What you can do
- Disaster Tracking — List official FEMA disaster declarations since 1953 and fetch detailed metadata for specific incidents natively
- Emergency Orchestration — List emergency management agencies by state to verify local coordination contacts flawlessly
- Assistance Analysis — Query housing assistance program data and individual assistance registrations to analyze recovery efforts natively
- Grant Inspection — Access hazard mitigation assistance projects and grant details to monitor community safety investments flawlessly
- Regional Insights — List official FEMA regions and web center locations to understand federal jurisdictional boundaries synchronously
- Public Data Access — Retrieve raw structured data from the official U.S. Federal Emergency Management Agency API without complex manual exports
The FEMA MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect FEMA to Pydantic AI via MCP
Follow these steps to integrate the FEMA MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from FEMA with type-safe schemas
Why Use Pydantic AI with the FEMA MCP Server
Pydantic AI provides unique advantages when paired with FEMA through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your FEMA integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your FEMA connection logic from agent behavior for testable, maintainable code
FEMA + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the FEMA MCP Server delivers measurable value.
Type-safe data pipelines: query FEMA with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple FEMA tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query FEMA and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock FEMA responses and write comprehensive agent tests
FEMA MCP Tools for Pydantic AI (11)
These 11 tools become available when you connect FEMA to Pydantic AI via MCP:
get_disaster_applications
Get statistics on disaster assistance applications
get_emergency_agencies
List emergency management agencies by state
get_fema_regions
List official FEMA regions
get_fema_web_centers
List FEMA web center locations
get_hazard_mitigation_grants
Get data on hazard mitigation assistance projects
get_housing_assistance
Get data regarding FEMA housing assistance programs
get_individuals_program
Get data on individuals and households program registrations
get_me
Get current API status
get_public_assistance_applicants
List applicants for FEMA public assistance
get_registration_intake
Get data from individual and household program registrations
list_disaster_declarations
List recent official FEMA disaster declarations
Example Prompts for FEMA in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with FEMA immediately.
"List recent disaster declarations in Florida."
"Get emergency management agency info for California."
"Show hazard mitigation projects in Texas."
Troubleshooting FEMA MCP Server with Pydantic AI
Common issues when connecting FEMA to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiFEMA + Pydantic AI FAQ
Common questions about integrating FEMA MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
Connect FEMA with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect FEMA to Pydantic AI
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.