How to Use the Keen MCP in LlamaIndex

Q: Can LlamaIndex search through past Keen query outputs?

Yes, the framework indexes outputs from tools like selectunique into your vector store. This lets you run semantic searches over past telemetry runs.

Q: Does LlamaIndex support real-time event logging to Keen?

Yes, the agent calls recordevent during execution to log interaction data. This updates your telemetry collections instantly.

Index live event data and query metrics directly within LlamaIndex using the Keen MCP Server.

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Connect Keen MCP to LlamaIndex

Create your Vinkius account to connect Keen 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 Keen with LlamaIndex

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Index live Keen query results into your LlamaIndex vector store

The `count_events` tool pulls raw telemetry numbers directly into your LlamaIndex documents. The framework converts these metrics into queryable nodes, ensuring your knowledge base stays updated with real-time data. Instead of parsing raw JSON, you ask questions in plain English and let the MCP server pull from cached results.

Build RAG pipelines grounded in actual Keen schemas

The `list_collections` tool provides the structural foundation for your data indexes. By mapping collection schemas, LlamaIndex understands exactly where your telemetry lives. Your agent uses `get_project_details` to verify project configurations. This grounds your generation step in actual database facts, completely eliminating hallucinated metrics.

Analyze cached datasets with LlamaIndex agents

The `list_datasets` tool exposes pre-computed event batches to your retrieval pipeline. The agent pulls these datasets directly into memory for quick analysis. It applies `average_property` and `sum_property` to calculate trends on the fly. You get a unified interface that merges static document retrieval with live numeric calculations.

Setup guide

Set up Keen 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 Keen 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 Keen tools.",
)
response = await agent.run("List recent Keen data")

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Common questions about Keen MCP in LlamaIndex

Install the LlamaIndex MCP tool spec package and connect to the Vinkius endpoint. Use the McpToolSpec class to convert the tools into a list your agent can use.

Yes, the framework indexes outputs from tools like `select_unique` into your vector store. This lets you run semantic searches over past telemetry runs.

Yes, the agent calls `record_event` during execution to log interaction data. This updates your telemetry collections instantly.

You can pass an allowed tools list to the McpToolSpec. This restricts the agent to specific operations like `count_unique` while blocking write actions.

Vinkius processes all event payloads through an ephemeral, zero-trust sandbox. Your database credentials and raw event properties are never exposed to public LLMs.

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