Tianyancha / 天眼查 MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Tianyancha / 天眼查 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 Tianyancha / 天眼查 "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Tianyancha / 天眼查?"
)
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 Tianyancha / 天眼查 MCP Server
Empower your AI agent to orchestrate your business intelligence and due diligence with Tianyancha (天眼查), the premier enterprise data platform in China. By connecting Tianyancha to your agent, you transform complex industrial research, ownership auditing, and risk monitoring into a natural conversation. Your agent can instantly search for companies, retrieve detailed registration metadata, browse shareholder structures, and monitor industrial abnormalities without you ever needing to navigate the comprehensive Tianyancha portal. Whether you are conducting B2B lead research or auditing potential partners, your agent acts as a real-time business intelligence assistant, keeping your data accurate and your decisions informed.
Pydantic AI validates every Tianyancha / 天眼查 tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- Enterprise Orchestration — Search for companies and retrieve detailed basic and industrial metadata.
- Ownership Auditing — Browse shareholder lists and outward investments to identify corporate structures.
- Personnel Monitoring — List main staff and executives to identify key decision-makers within an enterprise.
- Risk Management — Retrieve risk indicators, court cases, and industrial abnormalities for any registered company.
- IP Tracking — Browse registered trademarks, patents, and copyrights to audit intellectual property assets.
The Tianyancha / 天眼查 MCP Server exposes 10 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 Tianyancha / 天眼查 to Pydantic AI via MCP
Follow these steps to integrate the Tianyancha / 天眼查 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 10 tools from Tianyancha / 天眼查 with type-safe schemas
Why Use Pydantic AI with the Tianyancha / 天眼查 MCP Server
Pydantic AI provides unique advantages when paired with Tianyancha / 天眼查 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 Tianyancha / 天眼查 integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Tianyancha / 天眼查 connection logic from agent behavior for testable, maintainable code
Tianyancha / 天眼查 + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Tianyancha / 天眼查 MCP Server delivers measurable value.
Type-safe data pipelines: query Tianyancha / 天眼查 with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Tianyancha / 天眼查 tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Tianyancha / 天眼查 and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Tianyancha / 天眼查 responses and write comprehensive agent tests
Tianyancha / 天眼查 MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Tianyancha / 天眼查 to Pydantic AI via MCP:
get_basic_info
Get enterprise basic info
get_contact_info
Get enterprise contact info
get_full_details
Get full enterprise details
list_branches
List company branches
list_investments
List outward investments
list_ip
List intellectual property
list_risks
List enterprise risk info
list_shareholders
List company shareholders
list_staff
List main staff/executives
search_enterprise
Enterprise search by keyword
Example Prompts for Tianyancha / 天眼查 in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Tianyancha / 天眼查 immediately.
"Search for companies named 'Alibaba' in Tianyancha."
"Show me the shareholder structure for 'Huawei'."
"Check for any risk information regarding 'Evergrande'."
Troubleshooting Tianyancha / 天眼查 MCP Server with Pydantic AI
Common issues when connecting Tianyancha / 天眼查 to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiTianyancha / 天眼查 + Pydantic AI FAQ
Common questions about integrating Tianyancha / 天眼查 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 Tianyancha / 天眼查 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 Tianyancha / 天眼查 to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
