Qichacha / 企查查 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 Qichacha / 企查查 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 Qichacha / 企查查. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Qichacha / 企查查?"
)
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 Qichacha / 企查查 MCP Server
Empower your AI agent to orchestrate your business intelligence and due diligence with Qichacha (企查查), the premier enterprise data platform in China. By connecting Qichacha 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 Qichacha 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.
LlamaIndex agents combine Qichacha / 企查查 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
- Enterprise Orchestration — Fuzzy 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 Qichacha / 企查查 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 Qichacha / 企查查 to LlamaIndex via MCP
Follow these steps to integrate the Qichacha / 企查查 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 Qichacha / 企查查
Why Use LlamaIndex with the Qichacha / 企查查 MCP Server
LlamaIndex provides unique advantages when paired with Qichacha / 企查查 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Qichacha / 企查查 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Qichacha / 企查查 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Qichacha / 企查查, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Qichacha / 企查查 tools were called, what data was returned, and how it influenced the final answer
Qichacha / 企查查 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Qichacha / 企查查 MCP Server delivers measurable value.
Hybrid search: combine Qichacha / 企查查 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Qichacha / 企查查 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 Qichacha / 企查查 for fresh data
Analytical workflows: chain Qichacha / 企查查 queries with LlamaIndex's data connectors to build multi-source analytical reports
Qichacha / 企查查 MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Qichacha / 企查查 to LlamaIndex via MCP:
fuzzy_search
Enterprise fuzzy search
get_account_status
Get OpenAPI account status
get_basic_info
Get enterprise basic 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
Example Prompts for Qichacha / 企查查 in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Qichacha / 企查查 immediately.
"Search for companies named 'Xiaomi' in Qichacha."
"Show me the shareholder structure for 'Tencent'."
"Check for any risk information regarding 'Ant Group'."
Troubleshooting Qichacha / 企查查 MCP Server with LlamaIndex
Common issues when connecting Qichacha / 企查查 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpQichacha / 企查查 + LlamaIndex FAQ
Common questions about integrating Qichacha / 企查查 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 Qichacha / 企查查 with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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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 Qichacha / 企查查 to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.