PostHog MCP. Analyze user behavior conversationally
PostHog MCP connects your AI client directly to your product analytics data. List saved insights, track specific users, check feature flag status, and audit recent events using natural conversation. Get full control of your user behavior metrics without leaving your agent.
Give Claude and any AI agent real-world access
Retrieve deep details for specific insights, like conversion funnels or retention charts.
Get a complete profile on any identified person, seeing all their properties and behavior data.
List every defined feature flag and confirm whether it's currently active or disabled.
Check the status of all experiments, both running and completed, to measure impact.
List the most recent events captured by your project, verifying data ingestion or specific user steps.
Ask an AI about this
Waiting for input…
What AI agents can do with PostHog: 10 Tools for Deep Analytics
These tools give your agent the specific abilities needed to list events, track users, manage features, and retrieve every kind of product metric in PostHog.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using PostHog MCPGet Event
Pulls detailed information for one specific user action (event).
Get Insight
Retrieves the full details of a single saved analysis insight.
Get Person
Gets all known properties and data for one specific identified user.
List Actions
Lists every defined custom action that users can take in the product.
List Dashboards
Shows a list of all existing dashboards within your PostHog project.
List Events
Retrieves a list of the most recent user events captured by the system.
List Experiments
Shows all active and previously run product experiments.
List Feature Flags
Lists every feature flag configured for your project.
List Insights
Retrieves a list of all saved analytic insights available in the project.
List Persons
Lists all identified users or persons tracked by PostHog.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with PostHog, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PostHog. 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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The pain of context switching on product data
Today, checking basic user behavior is a manual mess. You open PostHog, navigate to the 'Insights' tab for funnels, then switch over to the 'People' section to check properties, and finally jump back to the main dashboard just to see if an experiment ran successfully. It takes five tabs and at least ten minutes.
With this MCP, you ask your agent a single question—like, 'What were the top three drop-off points in the signup funnel?' The data comes back immediately in plain language. You get the answer without ever leaving your chat window.
Get clear answers on feature flags with PostHog MCP
Before this, confirming a flag's status meant checking multiple sections or asking a developer to manually verify it in the UI. It was slow and prone to human error.
Now you simply ask your agent to list feature flags. The response is definitive: it tells you exactly what's on, what's off, and who sees it. There's no ambiguity.
What PostHog MCP does for your AI
This MCP lets you take over your product analytics from right inside your development workflow. Forget switching tabs or writing SQL queries just to answer a simple question about user adoption. You can talk to your AI client and get real-time data on how people use your app.
Need to know if the new checkout flow is working? Ask it. Want to check which feature flags are currently active? Just ask. This connector handles everything, giving you instant access to trends, funnels, and user property details. When you connect this MCP via Vinkius, your AI agent treats your product data like a native API endpoint—it's just part of the conversation.
You can audit recent activity logs or pull detailed metadata on any saved insight instantly.
019d75f8-62e2-7219-a3e9-9995ab04e764 How to set up PostHog MCP
The bottom line is you talk to your agent, and it pulls specific analytics directly from your PostHog project.
Subscribe to this MCP and input your PostHog Personal API Key and Project ID.
If needed, provide the PostHog Host URL for regional instances (like EU).
Your AI client can now analyze product data conversationally—just ask it a question.
Who uses PostHog MCP
Product Managers who need quick status checks on feature flags. Growth Engineers debugging user flows right in their IDE. Data Analysts who want to audit event logs without leaving their terminal.
Checks if the 'beta-search' flag is active or reviews the results of a recent signup funnel insight.
Monitors an active experiment and verifies user properties for specific person IDs during development sprints.
Audits the most recent event logs to confirm data pipeline integrity or pulls metadata on a specific insight type.
Benefits of connecting PostHog MCP
Stop writing repetitive queries. You can ask your agent to list insights and get detailed metadata (like funnels or trends) instantly.
No more manual lookups for users. Simply request details on a specific person, and the MCP provides their full profile, including key properties.
Manage product rollouts without context switching. Check the status of all feature flags directly by asking to list them, confirming if 'new-onboarding' is live or disabled.
Verify data integrity immediately. Use the tool to list recent project events and confirm that user actions are logging correctly.
Understand your testing efforts better. The MCP lets you list experiments so you can track product improvements and results without leaving your workflow.
PostHog MCP use cases
Debugging a broken signup funnel
A growth engineer needs to know why signups dropped last night. They ask their agent to list insights, focusing on funnels. The agent retrieves the 'Signup Funnel' insight and reports that retention charts show a drop-off at step 3.
Auditing data ingestion after an outage
A data analyst suspects event logging failed. They ask their agent to list recent project events. The MCP quickly returns the last 50 actions, allowing them to verify that user activity resumed correctly.
Checking feature rollout status for a release
A product manager needs confirmation before launch. They ask their agent to list feature flags and confirm that 'beta-search' is active only for the QA team, not general users.
Investigating a high-value user's behavior
A PM wants to understand why one specific enterprise client (a person ID) is using the product differently. They ask their agent to get details for that person, retrieving all associated properties and historical data points.
PostHog MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Over-reliance on dashboard summaries
The analyst assumes the main PostHog dashboard shows everything. They spend 15 minutes clicking through multiple tabs to find a single user property.
Instead, ask your agent to get details for a specific person ID. This MCP pulls the raw, granular data directly into your conversation.
Guessing feature flag status
The team debates if 'new-dashboard' is live or not, forcing a manual check with multiple stakeholders.
Use the MCP to list all feature flags. The agent gives you a definitive list and their current configuration status instantly.
When to use PostHog MCP
You should use this MCP if your core job requires translating complex product analytics into simple, actionable answers without context switching. If you constantly jump between PostHog's UI, your terminal, and a Slack chat, this is for you. Use it when you need to list insights, check user properties, or monitor feature flags programmatically.
Don't use this if you just need raw data dumps for external BI tools (use a direct API connection). Also, don't expect it to write new code; it only reads and summarizes the metrics that already exist. It's an analytical layer, not a development tool.
Frequently asked questions about PostHog MCP
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.