4,000+ servers built on vurb.ts
Vinkius

HHS Open Payments MCP Server for CrewAIGive CrewAI instant access to 6 tools to Download Dataset, Get Dataset, List Datasets, and more

MCP Inspector GDPR Free for Subscribers

Connect your CrewAI agents to HHS Open Payments through Vinkius, pass the Edge URL in the `mcps` parameter and every HHS Open Payments tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Ask AI about this MCP Server for CrewAI

The HHS Open Payments MCP Server for CrewAI is a standout in the Government Public Data category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
python
from crewai import Agent, Task, Crew

agent = Agent(
    role="HHS Open Payments Specialist",
    goal="Help users interact with HHS Open Payments effectively",
    backstory=(
        "You are an expert at leveraging HHS Open Payments tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in HHS Open Payments "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
HHS Open Payments
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

About HHS Open Payments MCP Server

Connect to the HHS Open Payments database to explore financial transparency in healthcare. This server allows you to query datasets, search for specific physicians or teaching hospitals, and analyze payments made by drug and device companies.

When paired with CrewAI, HHS Open Payments becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call HHS Open Payments tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

  • Dataset Discovery — List all available Open Payments datasets and inspect their metadata, including column definitions and update timestamps.
  • Physician & Hospital Search — Search for specific healthcare providers or teaching hospitals by name to find their associated records.
  • Advanced Querying — Use Socrata Query Language (SoQL) to filter, sort, and limit data for precise financial analysis.
  • Data Export — Download specific datasets in CSV, JSON, or XML formats for external processing or reporting.
  • Metadata Inspection — Fetch detailed information about specific datasets to understand the underlying data structure.

The HHS Open Payments MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 HHS Open Payments tools available for CrewAI

When CrewAI connects to HHS Open Payments through Vinkius, your AI agent gets direct access to every tool listed below — spanning financial-transparency, healthcare-data, compliance, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

download

Download dataset on HHS Open Payments

JSON is recommended for programmatic access. Download a specific Open Payments dataset

get

Get dataset on HHS Open Payments

Get metadata for a specific Open Payments dataset

list

List datasets on HHS Open Payments

List all available Open Payments datasets

query

Query dataset on HHS Open Payments

Query specific records within a dataset using SoQL

search

Search hospitals on HHS Open Payments

Search for specific teaching hospitals

search

Search physicians on HHS Open Payments

Search for specific physicians

Connect HHS Open Payments to CrewAI via MCP

Follow these steps to wire HHS Open Payments into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 6 tools from HHS Open Payments

Why Use CrewAI with the HHS Open Payments MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with HHS Open Payments through the Model Context Protocol.

01

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

02

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

03

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

04

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

HHS Open Payments + CrewAI Use Cases

Practical scenarios where CrewAI combined with the HHS Open Payments MCP Server delivers measurable value.

01

Automated multi-step research: a reconnaissance agent queries HHS Open Payments for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

02

Scheduled intelligence reports: set up a crew that periodically queries HHS Open Payments, analyzes trends over time, and generates executive briefings in markdown or PDF format

03

Multi-source enrichment pipelines: chain HHS Open Payments tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

04

Compliance and audit automation: a compliance agent queries HHS Open Payments against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for HHS Open Payments in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with HHS Open Payments immediately.

01

"List all available Open Payments datasets."

02

"Search for physicians named 'Gregory House' in the database."

03

"Query dataset pgaw-6u8r for payments in Florida where the amount is over $5,000."

Troubleshooting HHS Open Payments MCP Server with CrewAI

Common issues when connecting HHS Open Payments to CrewAI through Vinkius, and how to resolve them.

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

HHS Open Payments + CrewAI FAQ

Common questions about integrating HHS Open Payments MCP Server with CrewAI.

01

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
02

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
03

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
04

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
05

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

Explore More MCP Servers

View all →