FamilySearch API MCP Server for Pydantic AI 6 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect FamilySearch API through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to FamilySearch API "
"(6 tools)."
),
)
result = await agent.run(
"What tools are available in FamilySearch API?"
)
print(result.data)
asyncio.run(main())
* 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 FamilySearch API MCP Server
Empower your AI agent to orchestrate your entire genealogical research and ancestry auditing workflow with the FamilySearch API, the world's largest platform for family history. By connecting FamilySearch to your agent, you transform complex ancestor searches into a natural conversation. Your agent can instantly retrieve person details, audit pedigree charts, and query historical record collections without you ever touching a genealogy portal. Whether you are building your family tree or conducting deep-dive historical audits, your agent acts as a real-time genealogical consultant, ensuring your data is always verified and precise.
Pydantic AI validates every FamilySearch API 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.
What you can do
- Person Auditing — Search for millions of persons in the FamilySearch global tree and retrieve detailed metadata, including lifespans and birth/death places.
- Pedigree Oversight — Audit the ancestry charts for specific individuals to maintain a clear view of lineage distribution and scale.
- Memories Discovery — Retrieve photos, stories, and documents associated with specific persons to identify relevant assets instantly.
- Record Intelligence — List available historical record collections to understand the organizational reach of global archives.
- Metadata Intelligence — Retrieve unique identifiers and display names for any genealogical record to assist in deep-dive classification.
The FamilySearch API MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect FamilySearch API to Pydantic AI via MCP
Follow these steps to integrate the FamilySearch API MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 6 tools from FamilySearch API with type-safe schemas
Why Use Pydantic AI with the FamilySearch API MCP Server
Pydantic AI provides unique advantages when paired with FamilySearch API through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your FamilySearch API integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your FamilySearch API connection logic from agent behavior for testable, maintainable code
FamilySearch API + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the FamilySearch API MCP Server delivers measurable value.
Type-safe data pipelines: query FamilySearch API with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple FamilySearch API tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query FamilySearch API and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock FamilySearch API responses and write comprehensive agent tests
FamilySearch API MCP Tools for Pydantic AI (6)
These 6 tools become available when you connect FamilySearch API to Pydantic AI via MCP:
check_api_status
Check if the FamilySearch API is operational
get_person_details
Get full details for a specific person in the family tree by ID
get_person_memories
Get memories (photos, stories) associated with a person
get_person_pedigree
Get the ancestry (pedigree) for a specific person
list_historical_collections
List historical record collections available on FamilySearch
search_persons
Search for persons in the FamilySearch Family Tree
Example Prompts for FamilySearch API in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with FamilySearch API immediately.
"Search for 'George Washington' in FamilySearch."
"Show the pedigree for person ID 'KWCX-S58'."
"List available memories for person ID 'LZDP-H7Z'."
Troubleshooting FamilySearch API MCP Server with Pydantic AI
Common issues when connecting FamilySearch API to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiFamilySearch API + Pydantic AI FAQ
Common questions about integrating FamilySearch API MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect FamilySearch API with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect FamilySearch API to Pydantic AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.