Can I record a single event using this agent?

Yes, the `record_event` tool allows you to send a JSON object representing your event directly to any named collection.

How do I calculate the average value of a property?

Use the `average_property` tool by specifying the collection name and the numeric target property you want to average.

Is it possible to see my project's collections?

Absolutely. The `list_collections` tool retrieves a list of all event types (collections) currently stored in your Keen project.

Keen MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Keen
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Keen through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "keen": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Keen, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Keen MCP Server

Connect your Keen.io project to any AI agent to automate data collection and analysis. This MCP server allows your agent to record events and run complex analytical queries (count, sum, average, etc.) directly from natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Keen through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Event Recording — Send custom event data to any collection in your project instantly
Compute Metrics — Run aggregation queries like count, sum, and average on your event data
Data Discovery — List all event collections, saved queries, and cached datasets
Insight Extraction — Retrieve unique values for specific properties to understand data distribution
Project Oversight — Get comprehensive metadata and configuration details for your Keen project

The Keen MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 Keen to LangChain via MCP

Follow these steps to integrate the Keen MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Keen via MCP

Why Use LangChain with the Keen MCP Server

LangChain provides unique advantages when paired with Keen through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Keen MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Keen queries for multi-turn workflows

Keen + LangChain Use Cases

Practical scenarios where LangChain combined with the Keen MCP Server delivers measurable value.

RAG with live data: combine Keen tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Keen, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Keen tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Keen tool call, measure latency, and optimize your agent's performance

Keen MCP Tools for LangChain (10)

These 10 tools become available when you connect Keen to LangChain via MCP:

average_property

Calculate average of a property

count_events

Count total events in a collection

count_unique

Count unique values for a property

get_project_details

Get project configuration and details

list_collections

List all event collections

list_datasets

List cached datasets

list_saved_queries

List all saved queries

record_event

Record a single event to a collection

select_unique

List all unique values for a property

sum_property

Sum numeric values of a property

Example Prompts for Keen in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Keen immediately.

"Record a 'purchase' event with price 99.99 and user 'user_123' in Keen."

"What is the total count of 'page_view' events?"

"Show me all saved queries in my project."

Troubleshooting Keen MCP Server with LangChain

Common issues when connecting Keen to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Keen + LangChain FAQ

Common questions about integrating Keen MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.