Bring B2b Data
to Pydantic AI
Learn how to connect People Data Labs to Pydantic AI and start using 14 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 People Data Labs MCP Server?
Connect People Data Labs to your AI agent to access one of the most comprehensive B2B datasets available. Enrich profiles, identify prospects, and search through millions of person and company records using natural language.
What you can do
- Person Enrichment — Retrieve full professional profiles using just an email, phone number, or social media URL (LinkedIn, Twitter, etc.).
- Company Intelligence — Get detailed company metadata, including industry, size, location, and stock tickers.
- Advanced Search — Query the entire Person or Company dataset using SQL or Elasticsearch DSL directly from your conversation.
- Identity Resolution — Identify multiple potential profiles associated with a set of attributes to find the best match.
- Bulk Operations — Enrich up to 100 person or company records in a single request for high-scale workflows.
How it works
- Subscribe to this server
- Enter your People Data Labs API Key
- Start enriching your CRM data or building lead lists from Claude, Cursor, or any MCP client
Who is this for?
- Sales & Marketing Teams — Instantly enrich inbound leads or build targeted outbound lists without manual research.
- Recruiters — Find detailed candidate histories and contact information directly from your workflow.
- Data Engineers — Perform complex dataset queries and cleaning operations using SQL through an AI interface.
Built-in capabilities (14)
Get autocomplete suggestions for Search API query values
Bulk enrich up to 100 companies
Bulk enrich up to 100 persons
Clean and standardize raw company data
Clean and standardize raw location data
Clean and standardize raw school data
Enrich a company profile
Enrich an IP address
Enrich a job title to find similar titles and relevant skills
Enrich a person profile using attributes
Returns match_score. Identify multiple possible person profiles
Provide either an Elasticsearch DSL query or a SQL query. Search the Company Dataset using Elasticsearch DSL or SQL
Search active and historical job postings
Provide either an Elasticsearch DSL query or a SQL query. Search the Person Dataset using Elasticsearch DSL or SQL
Why Pydantic AI?
Pydantic AI validates every People Data Labs tool response against typed schemas, catching data inconsistencies at build time. Connect 14 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 People Data Labs 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 People Data Labs connection logic from agent behavior for testable, maintainable code
People Data Labs in Pydantic AI
People Data Labs and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect People Data Labs 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 | 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 People Data Labs in Pydantic AI
The People Data Labs 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 14 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
People Data Labs for Pydantic AI
Every tool call from Pydantic AI to the People Data Labs MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I enrich a profile using only a LinkedIn URL?
Yes! Use the pdl_enrich_person tool and provide the LinkedIn URL in the profile parameter. The agent will return the full professional profile associated with that URL.
Is it possible to search for companies by industry and size using SQL?
Absolutely. Use the pdl_search_company tool and provide a SQL query like SELECT * FROM company WHERE industry='software' AND employee_count > 500. This gives you direct access to the full dataset.
How many records can I enrich at once in bulk?
You can enrich up to 100 records per request using the pdl_bulk_enrich_person or pdl_bulk_enrich_company tools by passing a JSON array of request objects.
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 People Data Labs MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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