How to Use the Umeng / 友盟+ MCP in LlamaIndex

Q: How does LlamaIndex help audit Umeng / 友盟+ campaigns?

LlamaIndex indexes the output of listpushtasks and getpushstatus. This means you can ask natural language questions like, 'What was the status of the campaign sent last Tuesday?' and get a precise answer from the data.

Q: Is Umeng / 友盟+ performance data suitable for LlamaIndex?

Yes. The MCP Server exposes key metrics like getactiveusers and getnewusers. LlamaIndex takes those structured outputs and makes them semantically searchable, allowing you to query trends across time.

Q: What Umeng / 友盟+ tools are available for LlamaIndex?

The MCP Server offers dedicated tools like sendpush (for executing actions) and comprehensive read tools such as geteventdata, which feed into your index.

Ground your Umeng / 友盟+ queries in API facts with LlamaIndex.

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Connect Umeng / 友盟+ MCP to LlamaIndex

Create your Vinkius account to connect Umeng / 友盟+ to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Umeng / 友盟+ with LlamaIndex

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Search Past Campaign Results with MCP Server

Instead of just viewing a list, you can index the results. When you query for past tasks using `list_push_tasks`, that output becomes part of your searchable knowledge base. You'll get answers grounded in actual campaign data, not generic text.

Understand User Behavior Trends

Need to know why retention dipped last quarter? By indexing the results from `get_retention` and combining that with historical `get_duration_stats`, you build a unified index. This lets you query complex relationships between user longevity and session patterns.

Build an App Performance Knowledge Base

The app summary (`get_app_summary`) is critical, but it's better indexed. You can combine this general data with specific `get_event_data` records into one searchable index. Your agent queries both the high-level overview and the granular details simultaneously.

Setup guide

Set up Umeng / 友盟+ MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Umeng / 友盟+ MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Umeng / 友盟+ tools.",
)
response = await agent.run("List recent Umeng / 友盟+ data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Umeng / 友盟+. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Umeng / 友盟+ MCP in LlamaIndex

LlamaIndex indexes the output of `list_push_tasks` and `get_push_status`. This means you can ask natural language questions like, 'What was the status of the campaign sent last Tuesday?' and get a precise answer from the data.

Yes. The MCP Server exposes key metrics like `get_active_users` and `get_new_users`. LlamaIndex takes those structured outputs and makes them semantically searchable, allowing you to query trends across time.

You can. The MCP tool output becomes a chunk of knowledge that lives alongside your internal documentation. This creates an application where live API data and static PDFs are queried together.

The MCP Server offers dedicated tools like `send_push` (for executing actions) and comprehensive read tools such as `get_event_data`, which feed into your index.

This server touches user behavioral metrics, specifically custom event data retrieved via `get_event_data`.

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