Weiban Assistant MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Weiban Assistant as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Weiban Assistant. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Weiban Assistant?"
)
print(response)
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 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.
LlamaIndex agents combine Weiban Assistant tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Weiban Assistant MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Weiban Assistant MCP Server
LlamaIndex provides unique advantages when paired with Weiban Assistant through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Weiban Assistant tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Weiban Assistant tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Weiban Assistant, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Weiban Assistant tools were called, what data was returned, and how it influenced the final answer
Weiban Assistant + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Weiban Assistant MCP Server delivers measurable value.
Hybrid search: combine Weiban Assistant real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Weiban Assistant to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Weiban Assistant for fresh data
Analytical workflows: chain Weiban Assistant queries with LlamaIndex's data connectors to build multi-source analytical reports
Weiban Assistant MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Weiban Assistant to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Weiban Assistant to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWeiban Assistant + LlamaIndex FAQ
Common questions about integrating Weiban Assistant MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Weiban Assistant 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 Weiban Assistant to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.