Compatible with every major AI agent and IDE
What is the Namsor MCP Server?
Connect your Namsor account to any AI agent and simplify your name analytics and demographic enrichment through natural conversation.
What you can do
- Gender Prediction — Analyze first and last names to determine gender with high accuracy and probability metrics
- Origin & Residency — Predict a name's country of origin and likely current country of residency
- Ethnicity Tracking — Query US-specific ethnicity models (Hispanic, Asian, Black, White) for localized demographic insights
- Name Parsing — Break down complex full name strings into structured components (prefix, first, last, suffix)
- Diaspora Insights — Predict the diaspora group or ethnic cluster for a name within a specific country context
How it works
- Subscribe to this server
- Enter your Namsor API v2 Key from your account dashboard
- Start enriching your lead and customer data from Claude, Cursor, or any MCP-compatible client
Built-in capabilities (6)
Parse a full name string
Predict country residency from name
Predict diaspora from name
g., Hispanic, Asian, White). Predict US ethnicity from name
Predict gender from name
Predict country of origin from name
Why Pydantic AI?
Pydantic AI validates every Namsor tool response against typed schemas, catching data inconsistencies at build time. Connect 6 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.
- —
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 Namsor integration code
- —
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 Namsor connection logic from agent behavior for testable, maintainable code
Namsor in Pydantic AI
Namsor and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Namsor 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 Namsor in Pydantic AI
The Namsor 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 6 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
Namsor for Pydantic AI
Every tool call from Pydantic AI to the Namsor MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I predict gender using only a name?
Yes! Use the predict_gender tool. Provide the first and last name, and the agent will return the most likely gender and its probability.
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 Namsor 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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