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HHS Open Payments

HHS Open Payments MCP for AI. Audit financial ties in healthcare data.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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HHS Open Payments MCP on Cursor AI Code EditorHHS Open Payments MCP on Claude Desktop AppHHS Open Payments MCP on OpenAI Agents SDKHHS Open Payments MCP on Visual Studio CodeHHS Open Payments MCP on GitHub Copilot AI AgentHHS Open Payments MCP on Google Gemini AIHHS Open Payments MCP on Lovable AI DevelopmentHHS Open Payments MCP on Mistral AI AgentsHHS Open Payments MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

HHS Open Payments provides direct access to the HHS Open Payments database for financial transparency in healthcare. It lets users search records for specific physicians or teaching hospitals and analyze payment data made by drug and device companies.

You can list available datasets, download raw data structures (CSV, JSON), run precise queries using SoQL, and inspect metadata about the underlying public health records.

What your AI can do

Download dataset

Downloads a specified Open Payments dataset file in CSV, JSON, or XML format.

Get dataset

Retrieves the metadata and structure details for a specific Open Payments dataset.

List datasets

Lists all available datasets within the Open Payments database.

+ 3 more capabilities included
Discover available data sets

List and inspect the metadata of all Open Payments datasets.

Get dataset structure details

Fetch detailed information about a specific dataset to understand its column names and format.

Query records with filters

Run complex queries on a specified dataset, filtering results using SoQL syntax.

Search for medical providers

Find specific physicians within the database by name.

Search for hospitals

Locate records associated with specific teaching hospitals.

Export raw data files

Download a specified Open Payments dataset in CSV, JSON, or XML format.

Included with Plan

Waiting for input…

AI Agent

HHS Open Payments MCP: 6 Tools

Use these tools to list datasets, query specific records using filters, or download raw payment data from the HHS Open Payments database.

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Start using HHS Open Payments on Vinkius

Download Dataset

Downloads a specified Open Payments dataset file in CSV, JSON, or XML format.

Get Dataset

Retrieves the metadata and structure details for a specific Open Payments dataset.

List Datasets

Lists all available datasets within the Open Payments database.

Query Dataset

Runs targeted queries against a dataset, allowing filtering and sorting using SoQL.

Search Hospitals

Searches the database to find records associated with specific teaching hospitals.

Search Physicians

Finds and retrieves records for specific medical providers by name.

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Claude AI

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The HHS Open Payments integration is available immediately — no restart needed.

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HHS Open Payments MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HHS Open Payments. 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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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 6 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Finding financial relationships feels like sifting through government archives.

Right now, checking a single payment record means navigating multiple CMS portals. You have to search for the dataset ID, check its metadata to see if it contains location data, and then manually write complex filters just to narrow down payments by state or year. It's a lot of clicking through tabs and copy-pasting IDs.

With this MCP, you skip the portal mess entirely. You tell your agent exactly what you want—for example, 'Show me all payments over $10k in Florida.' The system handles the dataset discovery, the metadata check, and the filtering logic automatically. You get a clean, structured list of results without touching a government website.

HHS Open Payments: Structured Data Access

You don't have to manually track which dataset holds which type of payment or spend time debugging API calls for schema mismatches. The MCP groups all these functions, from `list_datasets` to the advanced `query_dataset`, into a single access point.

What changes is that you talk directly to your agent in plain English. You don't need to be an expert in Socrata Query Language or dataset IDs; you just ask for the answer.

What your AI can actually do with this

This MCP connects your agent to the HHS Open Payments database, letting you audit financial relationships across the healthcare industry. Instead of browsing complex government portals, you can ask for specific details—like payment amounts or connections between a specialist and a major hospital—and get structured results back immediately. You'll find tools to list all available datasets and download them in CSV, JSON, or XML formats for your reports.

Need to narrow down the scope? You can search specifically for physicians or teaching hospitals by name. For complex analysis, you use advanced querying features that filter records precisely using SoQL. When you connect this MCP via Vinkius, it acts as a single gateway, giving any compatible client access to all these public record tools without needing separate API keys for every function.

Built · Hosted · Managed by Vinkius HHS Open Payments - Audit Healthcare Financial Records
Server ID 019e38a8-3ce6-7120-a0b4-0767adf01998
Vinkius Inspector
Compliance Grade F
Score 43.65/100
Vinkius Inspector Badge — Score 43.65/100

Questions you might have

How do I find out what data fields are available using HHS Open Payments? +

You use get_dataset to retrieve metadata for a specific pool. This function shows you every column name, its definition, and whether it's a text or numeric field before you write any query.

Can I search for both doctors and hospitals with HHS Open Payments? +

Yes. You use search_physicians to find specific medical providers and search_hospitals to locate teaching facilities, pulling up records for both types of entities.

Is the data from HHS Open Payments real-time? +

The MCP accesses historical datasets. Use list_datasets first to check the update timestamps and determine if a dataset contains the most recent payment years you need.

Do I need an API key for querying data with HHS Open Payments? +

While not mandatory, providing an API Key is recommended. It helps increase your rate limit capacity when running repeated or high-volume queries using query_dataset.

What should I do if I run into rate limits when using `query_dataset`? +

You must implement exponential backoff and retry logic. If your AI client hits a limit, the system will return a specific error code; wait several seconds before re-running the query until it succeeds.

What are the supported file formats when I use `download_dataset`? +

You can request the data in CSV, JSON, or XML. For programmatic processing and reliability within your agent, JSON remains the recommended format for all exports.

How do I write complex filters or combine results using `query_dataset`? +

You use standard Socrata Query Language (SoQL) syntax. You can filter by multiple fields and apply logical operators like AND, OR, and NOT to narrow down your search criteria.

After calling `list_datasets`, how do I figure out which dataset is right for my specific research needs? +

You should use the get_dataset tool next. This retrieves detailed metadata, showing you exactly what columns and payment types each available Open Payments dataset contains.

Can I search for a specific doctor by name to see their financial records? +

Yes! Use the search_physicians tool with the doctor's name. The agent will return matching profiles and their associated payment data from the Open Payments database.

How do I filter data for a specific state or payment amount? +

You can use the query_dataset tool and provide a SoQL filter in the where parameter (e.g., recipient_state = 'NY' or total_amount_of_payment_usdollars > 1000).

What formats can I use to download the datasets? +

The download_dataset tool supports 'csv', 'json', and 'xml' formats. JSON is generally recommended for programmatic access and AI analysis.

Built & Managed by Vinkius 30s setup 6 tools

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