How to Use the GovInfo MCP in Pydantic AI

Q: How do I retrieve related legislative files?

Use getrelateddocuments to find connected packages. The framework ensures the relationship metadata matches the expected schema before returning it to your agent.

Get type-safe access to official US Government records inside your Pydantic AI MCP workflows.

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Connect GovInfo MCP to Pydantic AI

Create your Vinkius account to connect GovInfo to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup GovInfo with Pydantic AI

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Perplexity

Type-safe parsing with this MCP Server

When your agent queries federal databases, a single unexpected field can break your pipeline. This MCP Server integrates with Pydantic AI to validate every response from `get_package_summary` and `get_granule_summary` against strict schemas at runtime. If the government API returns a malformed date or an unexpected null value, your code catches it immediately instead of passing corrupted data downstream.

Validated semantic search

Run complex queries across federal archives without worrying about string-matching errors. Your Pydantic AI agent uses `search_documents` to locate relevant laws and immediately parses the JSON results into structured Python objects. Because the framework is model-agnostic, you can swap your underlying LLM while keeping the exact same validation rules for your `list_package_granules` calls.

Structured collection discovery

Mapping out government databases requires strict structural integrity. Your Pydantic AI agent uses `list_collections` to discover available archives and `get_collection` to pull documents within precise date ranges. Every single metadata field is validated before it hits your application logic, guaranteeing that your downstream analysis is built on verified, correctly formatted data.

Setup guide

Set up GovInfo MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "govinfo-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to GovInfo tools.",
)

result = await agent.run("List recent GovInfo transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by GovInfo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about GovInfo MCP in Pydantic AI

Use the MCPToolset class with your Vinkius HTTP endpoint and pass it to your Agent's toolsets list. The framework will automatically handle schema conversion.

Pydantic AI will raise a validation error immediately, preventing your agent from processing incorrect metadata or hallucinated fields.

Yes. Since the framework is model-agnostic, you can run your validated searches using local models or any major cloud LLM provider.

Use `get_related_documents` to find connected packages. The framework ensures the relationship metadata matches the expected schema before returning it to your agent.

The MCP Server only accesses public US federal publications, so you aren't sending proprietary data to the government. Vinkius runs the server in an ephemeral sandbox, securing your endpoint tokens and preventing any query logging.

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