How do I find my Weiban Corp ID and Secret?

Log in to your Weiban administration backend, go to [App Center] → [Open Platform], and you will find your Corp ID and Secret there. Ensure you have the necessary permissions enabled.

Can I see chat records through this server?

Yes. Use the `list_chat_records` tool to retrieve historical chat between staff members and customers. This is essential for auditing service quality and tracking sales conversations.

Is it possible to monitor group chat activity?

Yes! You can use the `list_group_chats` tool to see all active groups and `get_group_chat` with a specific ID to retrieve detailed information about participation and engagement levels.

Weiban Assistant MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Weiban Assistant
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 Weiban Assistant 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 Weiban Assistant "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Weiban Assistant?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Weiban Assistant MCP Server

Empower your AI agent to orchestrate your customer relationship within the WeCom ecosystem with Weiban Assistant, the leading CRM solution for business WeChat. By connecting Weiban to your agent, you transform complex customer tracking and group chat management into a natural conversation. Your agent can instantly list your customers, retrieve detailed lead information, monitor group chat activity, and even provide staff behavior statistics without you ever needing to navigate the web interface. Whether you are managing high-volume customer inquiries or complex sales pipelines, your agent acts as a real-time sales and service assistant, keeping your data accurate and your team responsive.

Pydantic AI validates every Weiban Assistant 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

Customer Orchestration — List and retrieve detailed information about your WeCom customers and external users.
Pipeline Management — Manage sales leads with full support for listing and creating new prospects.
Group Chat Monitoring — List active group chats and retrieve detailed information about participation and activity.
Staff Analytics — Monitor staff behavior statistics and performance metrics across the organization.
Activity Auditing — Browse chat records and retrieve high-level summaries of organization-wide WeCom engagement.

The Weiban Assistant 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 Weiban Assistant to Pydantic AI via MCP

Follow these steps to integrate the Weiban Assistant 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 Weiban Assistant with type-safe schemas

Why Use Pydantic AI with the Weiban Assistant MCP Server

Pydantic AI provides unique advantages when paired with Weiban Assistant 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 Weiban Assistant integration code

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

Dependency injection system cleanly separates your Weiban Assistant connection logic from agent behavior for testable, maintainable code

Weiban Assistant + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Weiban Assistant MCP Server delivers measurable value.

Type-safe data pipelines: query Weiban Assistant with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Weiban Assistant tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Weiban Assistant and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Weiban Assistant responses and write comprehensive agent tests

Weiban Assistant MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Weiban Assistant to Pydantic AI via MCP:

create_lead

Create a new lead

get_customer_details

Get customer details

get_group_chat

Get group chat details

get_org_summary

Get organization activity summary

get_staff_stats

Get staff behavior statistics

list_chat_records

List chat histories

list_customers

List WeCom customers

list_group_chats

List WeCom group chats

list_leads

List sales leads

list_staff

List organization staff

Example Prompts for Weiban Assistant in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Weiban Assistant immediately.

"List all my WeCom customers from Weiban."

"Show me the behavior statistics for staff user 'Mario'."

"Check the activity summary for our group chats."

Troubleshooting Weiban Assistant MCP Server with Pydantic AI

Common issues when connecting Weiban Assistant to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Weiban Assistant + Pydantic AI FAQ

Common questions about integrating Weiban Assistant 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 Weiban Assistant MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.