Compatible with every major AI agent and IDE
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_locationsandget_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_rawandget_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)
Retrieve metadata about how a dataset was ingested
Retrieve original unmodified source payload for a harvest record
Retrieve transformed DCAT-US payload for a harvest record
Retrieve commonly used keywords and their dataset counts
Retrieve the GeoJSON boundary for a specific location ID
Retrieve the complete list of publishing organizations
Search the catalog using keywords, filters, and sorting
Autocomplete search for location names to use with spatial filtering
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Data.gov Catalog through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
- —
The largest ecosystem of integrations, chains, and agents. combine Data.gov Catalog MCP tools with 500+ LangChain components
- —
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
- —
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
- —
Memory and conversation persistence let agents maintain context across Data.gov Catalog queries for multi-turn workflows
Data.gov Catalog in LangChain
Data.gov Catalog and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Data.gov Catalog to LangChain 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.
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 |
Why teams choose Vinkius for Data.gov Catalog in LangChain
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 LangChain 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.

* 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
How Vinkius secures
Data.gov Catalog for LangChain
Every tool call from LangChain to the Data.gov Catalog MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
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 LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
Explore More MCP Servers
View all →
Woodpecker CI
34 toolsManage your Woodpecker CI instance — control pipelines, monitor agents, and configure repositories directly from your AI agent.

R2R
6 toolsEquip your AI with direct access to your R2R engine — execute vector searches, run precise RAG queries, and manage your documents.

Cisco Meraki
8 toolsManage cloud-managed networking via Cisco Meraki — track devices, monitor clients, and audit network health directly from any AI agent.

ContactOut
7 toolsFind personal emails and direct phone numbers for professionals on LinkedIn to build targeted outreach lists that convert.
