Where do I find my Project ID?

You can find your Project ID in PostHog under **Project Settings**. It is a numeric ID usually found at the top of the settings page.

Does this support PostHog EU instances?

Yes! Use the optional `POSTHOG_HOST` credential and set it to `https://eu.posthog.com`. By default, it uses the US host (`https://app.posthog.com`).

Can I see individual user properties?

Absolutely. Use the `get_person` tool with a Person ID to retrieve all properties, tags, and identification metadata for a specific user.

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

Name: PostHog
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 PostHog 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({
        "posthog": {
            "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 PostHog, 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 PostHog MCP Server

Connect your PostHog project to any AI agent and take full control of your product analytics and feature management through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with PostHog 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

Insight Exploration — List and retrieve detailed metadata for saved insights, including trends, funnels, and retention charts.
User Tracking — List identified persons and inspect their properties to understand individual user behavior.
Feature Management — Maintain a clear view of all feature flags and their current configurations.
Experiment Monitoring — List active and past experiments to track product improvements and results.
Event Auditing — List the most recent events captured by your project to verify data ingestion and user actions.

The PostHog 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 PostHog to LangChain via MCP

Follow these steps to integrate the PostHog 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 PostHog via MCP

Why Use LangChain with the PostHog MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine PostHog 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 PostHog queries for multi-turn workflows

PostHog + LangChain Use Cases

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

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

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

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

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

PostHog MCP Tools for LangChain (10)

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

get_event

Get details for a specific event

get_insight

Get details for a specific insight

get_person

Get details for a specific person

list_actions

List defined user actions

list_dashboards

List project dashboards

list_events

List recent project events

list_experiments

List all active and past experiments

list_feature_flags

List all feature flags

list_insights

) for the project. List PostHog insights

list_persons

List identified persons/users

Example Prompts for PostHog in LangChain

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

"List all saved insights in our PostHog project."

"Check the status of all feature flags."

"List the last 5 persons identified in our project."

Troubleshooting PostHog MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

PostHog + LangChain FAQ

Common questions about integrating PostHog 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.