PostHog MCP. Analyze user behavior without leaving your chat window.
PostHog lets your AI agent manage product analytics and feature flags entirely through natural conversation. Instead of jumping between dashboards to check user activity, audit flag rollouts, or review event payloads, you get a single source of truth for understanding how users behave within your app. It connects deep behavioral data analysis directly into your workflow.
Give Claude and any AI agent real-world access
Check the details of any existing or proposed feature flag, including its current enabled state and targeted user percentage.
Look up a person by their unique ID to see all their properties, last login time, and full event history.
List or review the definitions of dynamic user cohorts based on specific events or property filters.
Browse recent application events, filtering by event name and inspecting all associated properties for debugging or analysis.
Create annotations on the timeline to correlate specific metric changes with major deployments, launches, or incidents.
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What AI agents can do with PostHog Alternative: 13 Tools
These tools give you granular control over every aspect of your product data, allowing your agent to manage everything from feature flags to user annotations.
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 MCPCreate Annotation
Marks a specific date or event (like a deployment) on the timeline for easy correlation with metric changes.
Create Feature Flag
Sets up a new feature flag in your project, allowing you to control its rollout...
Delete Feature Flag
Irreversibly removes an existing feature flag from the system after confirming all...
Get Feature Flag
Retrieves detailed information about a specific feature flag using its numeric ID.
Get Person
Fetches all details and properties for an individual user when provided with their...
Get User
Checks your current API key by returning the basic profile information of the connected account owner.
List Annotations
Retrieves a list of all historical annotations, showing when and what important events were marked on the timeline.
List Cohorts
Shows you all defined behavioral cohorts in your account, including their names and...
List Events
Gets a list of recent tracked events, letting you filter by type or check the...
List Feature Flags
Lists every feature flag in your project, helping you audit which flags are active...
List Persons
Retrieves a paginated list of all users tracked in the system, including their...
List Projects
Displays a list of all separate analytics workspaces or projects within your PostHog account.
Update Feature Flag
Modifies an existing feature flag's details, such as changing its name, description, or enabled status.
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
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The Headache of Dashboard Hopping
Today, figuring out why user engagement dipped requires a painful routine. You're in the analytics dashboard checking event volume. Then you realize you need to know which feature flag controls that flow, so you have to switch tabs and manually filter by key. Next, you check the individual user profiles for examples, which means copying IDs and pasting them into another tool just to get their full activity timeline.
With this MCP, all of that manual clicking disappears. Your agent reads your request—'Check the new checkout flow.' It automatically orchestrates calls like `list_feature_flags` and then pulls relevant event data using `list_events`, giving you a unified answer in plain language. You get insights, not dashboards.
Conversational Control of PostHog
You no longer have to manually initiate the audit process. Instead of navigating through project lists and then running a separate query for cohort definitions, you ask your agent: 'Show me all currently defined cohorts that are based on purchase events.' The tool handles the sequence: finding projects via `list_projects`, listing cohorts with `list_cohorts`, and filtering them down to the relevant criteria.
The difference is control. You speak to your product data as if it were a conversation, and you get structured, actionable intelligence back immediately. It's instant depth.
What PostHog MCP does for your AI
Connecting your PostHog account gives your agent full control over product analytics, feature flags, and user cohorts without ever opening the main dashboard. You can talk to it about what's happening in your application—from tracking specific user journeys to auditing which features are rolling out where. Want to know if a recent deployment changed conversion rates? Just ask.
Need to see why a particular group of users isn't adopting a new feature? The agent finds the cohort and shows you their activity timeline. You can check individual user profiles, browse recent events by type, or even create historical annotations that link metric changes directly to product launches. Because this MCP is hosted on Vinkius, your agent connects once and instantly gains access to all these deep behavioral insights, making it feel like having a dedicated, expert data engineer sitting right next to you.
019d8470-5702-72c0-a53f-b394d6d2b9a5 How to set up PostHog MCP
The bottom line is you stop switching between dashboards; you just ask your AI client questions about your product data.
Subscribe to this MCP and provide your PostHog Personal API Key.
Connect your AI client (like Cursor or Claude) to the Vinkius catalog. The agent now has access to all the analytics tools.
Ask a natural language question, such as 'Show me all feature flags that are currently set to 50% rollout' and let the agent execute the necessary calls.
Who uses PostHog MCP
Product Managers who get frustrated auditing feature flag rollouts manually, or developers debugging complex user flows by sifting through raw event logs. If you spend too much time jumping between PostHog tabs just to answer a single product question, this is for you.
Auditing which feature flags are live and checking if the rollout percentage matches your launch plan. They use it to create annotations when a major feature ships.
Debugging complex user flows by inspecting event payloads or verifying person properties for a specific bug report without opening the PostHog UI.
Reviewing behavioral cohorts and checking recent events to build reports on user engagement metrics quickly.
Benefits of connecting PostHog MCP
Stop dashboard hopping. Instead of checking the UI for list_feature_flags status, you just ask your agent if a specific flag is enabled and what its current rollout percentage is.
Deep dive into users instantly. You can use get_person to look up any user ID and see their entire property list and activity timeline in one go, skipping manual profile navigation.
Build better groups faster. Rather than manually defining filters, you can ask the agent to review all behavioral cohorts using list_cohorts and understand if your segmentation is accurate.
Debugging is easier. When an event goes wrong, you don't need to browse; you simply tell the agent to list_events and filter by type or time to find the faulty payload properties.
Contextual reporting. You can use create_annotation right from your chat when a major release happens, ensuring that all future metric changes are automatically linked back to that specific product launch date.
PostHog MCP use cases
A Product Manager needs to audit a new feature.
The PM asks the agent: 'Show me all flags and which ones are running at 50% rollout.' The agent uses list_feature_flags and then checks the specific status of the desired flag using get_feature_flag, giving immediate confirmation without opening a single tab.
A Developer is debugging an intermittent bug.
The developer tells the agent: 'Find all events from user X that occurred in the last hour, specifically looking for failed purchase attempts.' The agent uses get_person to confirm the ID, and then runs list_events, immediately isolating the problematic event payload.
A Data Analyst needs to prove a marketing campaign worked.
The analyst asks: 'List all cohorts created in Q1.' The agent uses list_cohorts to show existing groupings, then helps review the definition of a key cohort by checking its underlying filters for accuracy.
PostHog MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Checking analytics via manual UI clicks
Opening PostHog in a browser, navigating to 'Feature Flags', clicking through dozens of flags, and then opening the 'Events' tab just to cross-reference data points.
Instead, ask your agent: 'What are all currently active feature flags that target users with premium status?' The agent uses list_feature_flags and filters based on properties in a single conversational query.
Relying on exported CSV reports
Exporting event data to a spreadsheet, spending time cleaning up timestamps, or manually matching user IDs across different tabs.
Ask the agent to list_events and filter by timestamp range. The data comes structured immediately in your chat window, ready for analysis without cleanup.
Ignoring historical context
Seeing a sudden dip in conversion rates but having no record of why it happened (was it a bug? A deployment?).
Use list_annotations and ask the agent to show all annotations for the last two weeks. This instantly correlates performance dips with known deployments or launches.
When to use PostHog MCP
Use this MCP if your primary job involves deep, multi-step analysis of user behavior: auditing feature flags, segmenting users into cohorts, and tracing event lifecycles to understand why a metric changed. It's perfect for Product Managers and Data Analysts who need real-time insight without context switching.
Don't use this if all you need is simple data retrieval, like 'What was the total number of signups yesterday?' For that, a simpler reporting tool might suffice. This MCP excels at complex relationship mapping (e.g., linking an event to a cohort definition and then marking it with an annotation). If your goal is just single-point data collection, this might be overkill.
Frequently asked questions about PostHog MCP
How do I check my permissions using PostHog MCP? +
You run the get_user tool. This simply returns details about your connected account, confirming that your API key is valid and showing what access level you currently have.
Can I list all available analytics workspaces with PostHog MCP? +
Yes, use the list_projects tool. This will show every separate project workspace tied to your main PostHog account ID.
What is the best way to review user activity using PostHog MCP? +
The most direct way is to use get_person. Provide the distinct ID, and the agent will return that individual's full property set and comprehensive event history.
Does PostHog MCP help me manage feature flags? +
Absolutely. You can list all existing features with list_feature_flags, create new ones using create_feature_flag, or update status via update_feature_flag—all conversationally.
How do I link product launches to metric changes? +
You use the create_annotation tool. This allows you to pin a specific event, like 'V4 Launch,' to a date marker so that any future trend analysis automatically links back to it.