Bring Background Screening
to Pydantic AI
Learn how to connect InfoVetted to Pydantic AI and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the InfoVetted MCP Server?
Connect your InfoVetted account to any AI agent and manage background checks through natural conversation.
What you can do
- Vetting Requests — List all vetting requests, create new background checks, check status, and cancel active vettings
- Screening Contacts — Manage contacts for screening with full profile data, create new screening contacts, and inspect individual records
- Package Management — Browse available vetting packages and their included checks
- Result Tracking — Monitor check results with pass/fail status and compliance details
- Activity History — View submission and completion timelines
How it works
1. Subscribe to this server
2. Enter your InfoVetted API Key
3. Start managing background checks from Claude, Cursor, or any MCP-compatible client
Who is this for?
- HR Teams — initiate background checks on candidates and track results
- Compliance Officers — monitor vetting status and ensure regulatory compliance
- Staffing Agencies — manage high-volume screening workflows through AI
Built-in capabilities (12)
Cancel a background check
Verify InfoVetted API status
g., "Engineering Team"). Create a new organization group
Initiate a background check
Add a new individual for screening
Get details for a specific individual
Check status of a vetting process
List active webhooks
List organizational contact groups
List individuals being screened
). List available background check types
List all background check requests
Why Pydantic AI?
Pydantic AI validates every InfoVetted tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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 InfoVetted 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 InfoVetted connection logic from agent behavior for testable, maintainable code
InfoVetted in Pydantic AI
InfoVetted and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect InfoVetted 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.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ 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 InfoVetted in Pydantic AI
The InfoVetted 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 12 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.
* 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
InfoVetted for Pydantic AI
Every tool call from Pydantic AI to the InfoVetted MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I initiate a background check through the AI agent?
Yes. Use create_new_vetting_check with the contact ID and vetting package to initiate a background check. Use create_screening_contact first if the person isn't in your system. Track progress with get_vetting_request_status.
Can I track the status of active vetting requests?
Yes. Use list_vetting_requests to see all requests with their current status. Use get_vetting_request_status for detailed progress on a specific check. Use cancel_active_vetting to stop a check that's no longer needed.
Can I manage screening contacts and their data?
Yes. Use list_screening_contacts to browse all contacts, get_screening_contact for individual profiles, and create_screening_contact to add new people to the system. Each contact can have multiple vetting requests associated.
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 InfoVetted MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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