OpenCorporates 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 OpenCorporates 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 OpenCorporates "
"(6 tools)."
),
)
result = await agent.run(
"What tools are available in OpenCorporates?"
)
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 OpenCorporates MCP Server
Empower your AI agent to orchestrate your entire corporate auditing and due diligence workflow with OpenCorporates, the world's largest open database of companies. By connecting OpenCorporates to your agent, you transform complex registration lookups into a natural conversation. Your agent can instantly search for companies across hundreds of jurisdictions, audit officer histories, and retrieve detailed corporate groupings without you ever touching a manual register. Whether you are conducting competitive analysis or background checks, your agent acts as a real-time corporate investigator, ensuring your business intelligence is always grounded in official, verified data.
Pydantic AI validates every OpenCorporates 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
- Corporate Auditing — Search for companies by name across global jurisdictions and retrieve detailed metadata, including registration numbers and current status.
- Officer Oversight — Search for directors and corporate officers to maintain a clear view of organizational leadership and history.
- Jurisdiction Discovery — List and query all supported jurisdictions to understand the geographic reach of your research.
- Grouping Intelligence — Retrieve details for corporate groupings to understand complex ownership structures instantly.
- Status Monitoring — Check your API token usage and account metadata to maintain strict control over your research volume.
The OpenCorporates 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 OpenCorporates to Pydantic AI via MCP
Follow these steps to integrate the OpenCorporates 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 OpenCorporates with type-safe schemas
Why Use Pydantic AI with the OpenCorporates MCP Server
Pydantic AI provides unique advantages when paired with OpenCorporates 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 OpenCorporates integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your OpenCorporates connection logic from agent behavior for testable, maintainable code
OpenCorporates + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the OpenCorporates MCP Server delivers measurable value.
Type-safe data pipelines: query OpenCorporates with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple OpenCorporates tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query OpenCorporates and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock OpenCorporates responses and write comprehensive agent tests
OpenCorporates MCP Tools for Pydantic AI (6)
These 6 tools become available when you connect OpenCorporates to Pydantic AI via MCP:
get_api_status
Check current API token usage and status
get_company_details
Get full details for a specific company by jurisdiction and number
get_corporate_grouping
Get details for a corporate grouping
list_jurisdictions
List all jurisdictions supported by OpenCorporates
search_companies
Search for companies by name or keyword
search_officers
Search for corporate officers and directors
Example Prompts for OpenCorporates in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with OpenCorporates immediately.
"Search for companies named 'Vinkius' using OpenCorporates."
"Show company details for 'google' in jurisdiction 'us_de' (Delaware)."
"Find corporate officers named 'John Smith'."
Troubleshooting OpenCorporates MCP Server with Pydantic AI
Common issues when connecting OpenCorporates to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiOpenCorporates + Pydantic AI FAQ
Common questions about integrating OpenCorporates 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 OpenCorporates 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 OpenCorporates to Pydantic AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.