Pydantic AISDK

Data.gov Catalog MCP Server

Bring Open Data
to Pydantic AI

Name: Data.gov Catalog MCP Server
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

Learn how to connect Data.gov Catalog to Pydantic AI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.

GDPR Free for Subscribers

Get Harvest RecordGet Harvest Record RawGet Harvest Record TransformedGet KeywordsGet Location GeometryGet OrganizationsSearch DatasetsSearch Locations

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Ask AI about this MCP Server ChatGPT Claude Perplexity

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

What is the Data.gov Catalog MCP Server?

Connect to the Data.gov Catalog to explore the comprehensive repository of US Government open data. This MCP server allows AI agents to discover datasets from agencies like NASA, NOAA, and the Census Bureau through natural language.

What you can do

Dataset Discovery — Search the entire catalog using keywords, organization filters, and advanced sorting via search_datasets.
Spatial Analysis — Find datasets by geographic location using GeoJSON boundaries and spatial filters with search_locations and get_location_geometry.
Organization Insights — List all publishing organizations and filter results by specific agency slugs using get_organizations.
Metadata Inspection — Retrieve detailed harvest records, including raw and transformed DCAT-US payloads with get_harvest_record_raw and get_harvest_record_transformed.
Keyword Trends — Analyze commonly used keywords and their dataset counts to identify data trends using get_keywords.

How it works

Subscribe to this server
Enter 'PUBLIC' or your API key if required by your proxy
Start querying the US Government's open data repository directly from Claude, Cursor, or any MCP-compatible client

Who is this for?

Data Scientists — quickly find relevant datasets for analysis without manual browsing
Researchers — access official government metadata and harvest records for academic or policy work
Developers — integrate public data sources into applications using structured GeoJSON and DCAT-US metadata

Built-in capabilities (8)

get_harvest_record

Retrieve metadata about how a dataset was ingested

get_harvest_record_raw

Retrieve original unmodified source payload for a harvest record

get_harvest_record_transformed

Retrieve transformed DCAT-US payload for a harvest record

get_keywords

Retrieve commonly used keywords and their dataset counts

get_location_geometry

Retrieve the GeoJSON boundary for a specific location ID

get_organizations

Retrieve the complete list of publishing organizations

search_datasets

Search the catalog using keywords, filters, and sorting

search_locations

Autocomplete search for location names to use with spatial filtering

Why Pydantic AI?

Pydantic AI validates every Data.gov Catalog tool response against typed schemas, catching data inconsistencies at build time. Connect 8 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.

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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Data.gov Catalog integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Data.gov Catalog connection logic from agent behavior for testable, maintainable code

See it in action

Data.gov Catalog in Pydantic AI

AI Agent→Vinkius

High Security·Kill Switch·Plug and Play

Why Vinkius

Data.gov Catalog and 4,000+ other MCP servers. One platform. One governance layer.

Teams that connect Data.gov Catalog to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.

4,000+MCP Servers ready

<40msCold start

60%Token savings

	Raw MCP	Vinkius
Server catalog	Find and host yourself	4,000+ managed
Infrastructure	Self-hosted	Sandboxed V8 isolates
Credential handling	Plaintext in config	Vault + runtime injection
Data loss prevention	None	Configurable DLP policies
Kill switch	None	Global instant shutdown
Financial circuit breakers	None	Per-server limits + alerts
Audit trail	None	Ed25519 signed logs
SIEM log streaming	None	Splunk, Datadog, Webhook
Honeytokens	None	Canary alerts on leak
Custom domains	Not applicable	DNS challenge verified
GDPR compliance	Manual effort	Automated purge + export

Unlock for AI Agents View step-by-step setup guide for Pydantic AI →

Enterprise Security

Why teams choose Vinkius for Data.gov Catalog in Pydantic AI

The Data.gov Catalog 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. All 8 tools execute in hardened sandboxes optimized for native MCP execution.

Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

Unlock for AI Agents View full Data.gov Catalog details →

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

The Vinkius Advantage

How Vinkius secures
Data.gov Catalog for Pydantic AI

Every tool call from Pydantic AI to the Data.gov Catalog MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.

< 40msCold start

Ed25519Signed audit chain

60%Token savings

FAQ

Frequently asked questions

Can I search for datasets within a specific geographic area?

Yes! Use search_locations to find a location ID, then get_location_geometry to get the GeoJSON. Finally, pass that to search_datasets with the spatial_geometry parameter.

How do I find datasets from a specific agency like NASA?

Use the search_datasets tool and provide 'nasa' in the org_slug parameter. You can combine this with a search query q for more specific results.

What is the difference between raw and transformed harvest records?

The get_harvest_record_raw tool returns the original metadata from the source agency, while get_harvest_record_transformed returns the data mapped to the standard DCAT-US schema used by Data.gov.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Data.gov Catalog MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.