Kissmetrics MCP Server for LangChain 7 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Kissmetrics through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"kissmetrics": {
"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 Kissmetrics, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Kissmetrics MCP Server
Connect your Kissmetrics account to any AI agent to automate your user behavioral analytics and tracking workflows. This MCP server enables your agent to record events, manage user properties, and query complex metric data directly from natural language interfaces.
LangChain's ecosystem of 500+ components combines seamlessly with Kissmetrics through native MCP adapters. Connect 7 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
- Behavior Tracking — Record custom events for specific users to monitor their journey and interactions
- Profile Management — Set and update user properties and metadata to maintain rich customer profiles
- Identity Resolution — Alias multiple identities to maintain a single, unified view of a user across sessions
- Data Discovery — List all defined event types and property names currently in your account
- Analytical Querying — Retrieve people counts and metric values over time to track business performance
The Kissmetrics MCP Server exposes 7 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 Kissmetrics to LangChain via MCP
Follow these steps to integrate the Kissmetrics 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 7 tools from Kissmetrics via MCP
Why Use LangChain with the Kissmetrics MCP Server
LangChain provides unique advantages when paired with Kissmetrics through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Kissmetrics 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 Kissmetrics queries for multi-turn workflows
Kissmetrics + LangChain Use Cases
Practical scenarios where LangChain combined with the Kissmetrics MCP Server delivers measurable value.
RAG with live data: combine Kissmetrics tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Kissmetrics, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Kissmetrics tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Kissmetrics tool call, measure latency, and optimize your agent's performance
Kissmetrics MCP Tools for LangChain (7)
These 7 tools become available when you connect Kissmetrics to LangChain via MCP:
alias_identities
g., linking a browser ID to an email). Link two identities together
list_event_types
List all event types defined in the account
list_property_names
List all property names used in the account
query_metric_data
Requires a metric ID and query parameters. Get data for a specific metric
query_people_count
Get the count of people matching specific criteria
record_event
Requires a person identity (email/ID) and an event name. Record a behavior event for a person
set_person_properties
Set properties for a specific person
Example Prompts for Kissmetrics in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Kissmetrics immediately.
"Record a 'Purchased' event for 'user@example.com' with price 49.99."
"Set the property 'Plan Tier' to 'Enterprise' for 'customer_123'."
"Show me all event types defined in my account."
Troubleshooting Kissmetrics MCP Server with LangChain
Common issues when connecting Kissmetrics to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersKissmetrics + LangChain FAQ
Common questions about integrating Kissmetrics MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Kissmetrics 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 Kissmetrics to LangChain
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.