Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Juhe Data / 聚合数据. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Juhe Data / 聚合数据?"
)
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 Juhe Data / 聚合数据 MCP Server
Empower your AI agent to access a vast array of essential data services with Juhe Data (聚合数据), the premier API aggregator in China. By connecting Juhe to your agent, you transform fragmented data retrieval into a natural conversation. Your agent can instantly check real-time weather and forecasts for any Chinese city, verify ID card registration details, lookup IP address locations, and retrieve the latest news across multiple categories. Whether you are automating background checks, monitoring local conditions, or staying updated with domestic trends, your agent acts as a real-time data intelligence assistant, providing accurate and reliable information from a single, unified source.
LlamaIndex agents combine Juhe Data / 聚合数据 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
- Weather Intelligence — Retrieve real-time weather and 3-day forecasts for cities across China.
- Identity Verification — Audit ID card numbers to retrieve area, sex, and birthday information.
- Geographical Insights — Lookup IP address locations to identify user regions and network providers.
- Content Aggregation — Retrieve the latest news headlines and articles across various categories.
- Calendar & Culture — Access lunar calendar data, holiday schedules, and even constellation horoscopes.
The Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 to LlamaIndex via MCP
Follow these steps to integrate the Juhe Data / 聚合数据 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 Juhe Data / 聚合数据
Why Use LlamaIndex with the Juhe Data / 聚合数据 MCP Server
LlamaIndex provides unique advantages when paired with Juhe Data / 聚合数据 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Juhe Data / 聚合数据 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Juhe Data / 聚合数据 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Juhe Data / 聚合数据, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Juhe Data / 聚合数据 tools were called, what data was returned, and how it influenced the final answer
Juhe Data / 聚合数据 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Juhe Data / 聚合数据 MCP Server delivers measurable value.
Hybrid search: combine Juhe Data / 聚合数据 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 for fresh data
Analytical workflows: chain Juhe Data / 聚合数据 queries with LlamaIndex's data connectors to build multi-source analytical reports
Juhe Data / 聚合数据 MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Juhe Data / 聚合数据 to LlamaIndex via MCP:
get_calendar_day
Get calendar and holiday info for a day
get_calendar_month
Get holiday info for a month
get_constellation_horoscope
Get constellation horoscope
get_driving_test_questions
Get random driving test questions
get_exchange_rate
Get currency exchange rate
get_id_card_info
Get ID card basic information
get_ip_lookup
Lookup IP address location
get_latest_news
Get latest news headlines
get_oil_price
Get latest oil prices in China
get_weather
Get weather information for a city
Example Prompts for Juhe Data / 聚合数据 in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Juhe Data / 聚合数据 immediately.
"What's the weather in Beijing today?"
"Check the information for ID card 110101199001011234."
"Show me the latest tech news from Juhe."
Troubleshooting Juhe Data / 聚合数据 MCP Server with LlamaIndex
Common issues when connecting Juhe Data / 聚合数据 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpJuhe Data / 聚合数据 + LlamaIndex FAQ
Common questions about integrating Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 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 Juhe Data / 聚合数据 to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.