How do I find my WeCom Corp ID and Secret?

Log in to the WeCom Admin Backend. Your Corp ID is in [My Company] → [Company Profile]. Your App Secret and Agent ID are in [Apps] → select your application.

Can I read attendance records for a group of users?

Yes. Use the `get_attendance_data` tool. You will need to provide a start time, end time, and a comma-separated list of user IDs to retrieve the records.

Does my application need specific permissions for messages?

Yes. Ensure your application has 'Messaging' permissions enabled in the WeCom Admin Backend and that the 'Trusted IPs' for your server are correctly configured.

WeCom / 企业微信 MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: WeCom / 企业微信
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect WeCom / 企业微信 through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 WeCom / 企业微信 "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in WeCom / 企业微信?"
    )
    print(result.data)

asyncio.run(main())

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* 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 WeCom / 企业微信 MCP Server

Empower your AI agent to orchestrate your enterprise operations with WeCom (Enterprise WeChat), the dominant business communication platform in China. By connecting WeCom to your agent, you transform complex organization management and internal communication into a natural conversation. Your agent can instantly list departments, retrieve employee profiles, monitor attendance data, and even send messages to staff members without you needing to navigate the comprehensive WeCom Admin Backend. Whether you are managing a large-scale workforce or a specific internal application, your agent acts as a real-time operations assistant, keeping your data accurate and your team aligned.

Pydantic AI validates every WeCom / 企业微信 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

Organization Orchestration — List all departments and retrieve detailed employee profiles across your company.
Staff Communication — Send instant text messages to any user in your organization directly through the chat interface.
Attendance Monitoring — Retrieve real-time check-in data for employees to audit workforce activity.
Tag & Group Management — Browse organization tags and identify users belonging to specific functional groups.
Application Insights — Retrieve metadata about your internal apps, including custom menu configurations.

The WeCom / 企业微信 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 WeCom / 企业微信 to Pydantic AI via MCP

Follow these steps to integrate the WeCom / 企业微信 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 WeCom / 企业微信 with type-safe schemas

Why Use Pydantic AI with the WeCom / 企业微信 MCP Server

Pydantic AI provides unique advantages when paired with WeCom / 企业微信 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 WeCom / 企业微信 integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your WeCom / 企业微信 connection logic from agent behavior for testable, maintainable code

WeCom / 企业微信 + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the WeCom / 企业微信 MCP Server delivers measurable value.

Type-safe data pipelines: query WeCom / 企业微信 with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple WeCom / 企业微信 tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query WeCom / 企业微信 and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock WeCom / 企业微信 responses and write comprehensive agent tests

WeCom / 企业微信 MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect WeCom / 企业微信 to Pydantic AI via MCP:

get_app_details

Get application agent details

get_attendance_data

Get employee attendance/checkin data

get_department

Get department info

get_tag_users

Get users with a specific tag

get_user

Get user details

list_departments

List all departments

list_menu

Get app custom menu

list_tags

List all organization tags

list_users

List users in a department

send_message

Send a text message to a user

Example Prompts for WeCom / 企业微信 in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with WeCom / 企业微信 immediately.

"List all departments in our organization."

"Send a message to user 'Mario' saying 'The deployment is complete'."

"Show me the attendance data for 'mario,renato' from today."

Troubleshooting WeCom / 企业微信 MCP Server with Pydantic AI

Common issues when connecting WeCom / 企业微信 to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

WeCom / 企业微信 + Pydantic AI FAQ

Common questions about integrating WeCom / 企业微信 MCP Server with Pydantic AI.

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 WeCom / 企业微信 MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.