GeTui / 个推 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 GeTui / 个推 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 GeTui / 个推. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in GeTui / 个推?"
)
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 GeTui / 个推 MCP Server
Empower your AI agent to orchestrate your push notification infrastructure with GeTui (个推), the dominant CPaaS and developer services provider in China. By connecting GeTui to your agent, you transform complex device targeting, message broadcasting, and delivery auditing into a natural conversation. Your agent can instantly send targeted notifications to specific users, broadcast messages to your entire user base, retrieve real-time delivery and click statistics, and monitor user online status without you ever needing to navigate the comprehensive GeTui Developer Center. Whether you are automating verification flows or coordinating large-scale promotional alerts, your agent acts as a real-time messaging assistant, keeping your communication flow accurate and your user insights up-to-date.
LlamaIndex agents combine GeTui / 个推 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
- Push Orchestration — Send targeted, list-based, or broadcast notifications with full support for custom payloads.
- User Status Monitoring — Retrieve real-time online/offline status and associate custom aliases with Client IDs (CIDs).
- Tag & Interest Auditing — Browse user tags to identify audience segments and interest patterns for refined targeting.
- Delivery Analytics — Access real-time statistics for push tasks, including delivery counts, display rates, and clicks.
- Growth Insights — Monitor application-wide statistics for new and active users across specific dates.
The GeTui / 个推 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 GeTui / 个推 to LlamaIndex via MCP
Follow these steps to integrate the GeTui / 个推 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 GeTui / 个推
Why Use LlamaIndex with the GeTui / 个推 MCP Server
LlamaIndex provides unique advantages when paired with GeTui / 个推 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GeTui / 个推 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GeTui / 个推 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GeTui / 个推, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GeTui / 个推 tools were called, what data was returned, and how it influenced the final answer
GeTui / 个推 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GeTui / 个推 MCP Server delivers measurable value.
Hybrid search: combine GeTui / 个推 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GeTui / 个推 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 GeTui / 个推 for fresh data
Analytical workflows: chain GeTui / 个推 queries with LlamaIndex's data connectors to build multi-source analytical reports
GeTui / 个推 MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect GeTui / 个推 to LlamaIndex via MCP:
bind_user_alias
g., username) with a Client ID. Bind alias to user
get_app_user_stats
Get application user stats
get_cid_status
Check user online status
get_daily_push_report
Get daily push report
get_push_status
Check push task status
get_user_tags
Get user tags
push_to_all
Broadcast push to all users
push_to_list
Send push to multiple users
push_to_single
Send push to single user
query_user_alias
Query user alias
Example Prompts for GeTui / 个推 in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GeTui / 个推 immediately.
"Send a push notification to CID '1a0918c...' with title 'Urgent Update'."
"Check the online status for user CID '9920a1b...'."
"Show me the push report for yesterday."
Troubleshooting GeTui / 个推 MCP Server with LlamaIndex
Common issues when connecting GeTui / 个推 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGeTui / 个推 + LlamaIndex FAQ
Common questions about integrating GeTui / 个推 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 GeTui / 个推 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 GeTui / 个推 to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.