Bring Epidemiology
to CrewAI
Learn how to connect CDC WONDER (Epidemiologic Data) to CrewAI and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the CDC WONDER (Epidemiologic Data) MCP Server?
Connect to the CDC WONDER (Wide-ranging Online Data for Epidemiologic Research) system to query massive public health databases through natural language.
What you can do
- Mortality Data — Query the D76 (Detailed Mortality) and D77 (Underlying Cause of Death) databases for specific timeframes and regions.
- Birth Statistics — Access the D10 (Natality) database to analyze birth rates and maternal health metrics.
- Vaccine Safety — Query the VAERS (Vaccine Adverse Event Reporting System) database for safety monitoring data.
- Structured Queries — Execute complex ad-hoc queries using standard CDC parameters (B_, M_, V_, F_, O_ prefixes) for precise data extraction.
- Epidemiologic Research — Retrieve raw data for analysis in scientific research, public health policy, or educational projects.
How it works
- Subscribe to this server
- Enter your CDC WONDER API Access Token (if required by your proxy) or accept the Data Use Agreement
- Start querying epidemiologic data from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Epidemiologists & Researchers — quickly pull mortality and birth statistics without navigating the complex WONDER web interface
- Public Health Officials — monitor health trends and vaccine safety reports directly from an AI assistant
- Data Scientists — fetch structured JSON epidemiologic data for integration into larger analytical workflows
Built-in capabilities (1)
g., D76 for Mortality). Provide the database ID and a JSON object of parameters (B_, M_, V_, F_, O_ prefixes). Query CDC WONDER epidemiologic databases
Why CrewAI?
When paired with CrewAI, CDC WONDER (Epidemiologic Data) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call CDC WONDER (Epidemiologic Data) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
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CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
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
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
CDC WONDER (Epidemiologic Data) in CrewAI
CDC WONDER (Epidemiologic Data) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect CDC WONDER (Epidemiologic Data) to CrewAI 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 CDC WONDER (Epidemiologic Data) in CrewAI
The CDC WONDER (Epidemiologic Data) 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 1 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI 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
CDC WONDER (Epidemiologic Data) for CrewAI
Every tool call from CrewAI to the CDC WONDER (Epidemiologic Data) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Which databases can I access using this server?
You can query any database supported by the CDC WONDER API by providing its ID to the query_wonder_database tool. Common IDs include D76 (Detailed Mortality), D10 (Natality), and VAERS (Vaccine Adverse Event Reporting System).
How should I format the parameters for a query?
Parameters should be provided as a JSON object using the standard CDC prefixes: B_ for by-variables, M_ for measures, V_ for values, F_ for filters, and O_ for other options. The query_wonder_database tool handles the XML conversion for you.
Do I need to include the 'accept_datause_restrictions' parameter?
No. The query_wonder_database tool is designed to handle the data use restrictions agreement internally. You only need to provide the specific database ID and the analytical parameters for your search.
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.
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.
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.
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.
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.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
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.
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