OpenReplay MCP for AI. Debug user sessions instantly from your chat agent.
Works with every AI agent you already use
…and any MCP-compatible client








How this MCP server connects to your AI agent
OpenReplay helps you debug web applications by letting your AI agent inspect recorded user sessions, technical events, and project data conversationally.
Stop digging through logs; just ask your agent what went wrong for a specific user or feature.
What AI agents can do with OpenReplay Automation
Get session
Retrieves basic metadata for one specific session recording.
List projects
Gets a list of all projects connected to your account, helping you narrow down the scope.
List session events
Pulls every technical action and user event recorded within an entire session.
Lists all web application environments or projects linked to your OpenReplay account.
Retrieves a list of recorded user sessions for a specific project, allowing you to filter results by User ID.
Locates and identifies specific users within your projects using their email addresses or unique IDs.
Pulls the metadata for a single, targeted user session recording.
Fetches all recorded technical and user actions, like clicks or console logs, that happened during a specific session.
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What AI agents can do with OpenReplay: 5 Tools for Deep Session Analysis
These tools let you systematically list projects, find users, track sessions, and retrieve every technical event recorded during a user's web visit.
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 OpenReplay on VinkiusGet Session
Retrieves basic metadata for one specific session recording.
List Projects
Gets a list of all projects connected to your account, helping you narrow down the...
List Session Events
Pulls every technical action and user event recorded within an entire session.
List Sessions
Retrieves a list of sessions for a specific project, giving you filters by User ID...
Search Users
Finds and verifies the existence of users within your projects using emails or IDs.
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.
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Make Your AI Do More
Start with OpenReplay, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by OpenReplay. 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.
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Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 5 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
The headache of chasing down technical bugs in session recordings., Solved with Vinkius AI Gateway
Today, finding out what went wrong is a nightmare. You start with a helpdesk ticket, copy the user ID, then switch tabs to the OpenReplay dashboard. You filter by date, you try to find that specific project environment, and you end up clicking through dozens of session lists just to confirm if the bug even happened last week.
With this MCP, your AI agent takes over the tedious parts. Instead of manual searching, you simply ask for the data you need—like 'Show me sessions from User 12 in Project X.' Your agent pulls the context and gives you a starting point that's ready to analyze.
OpenReplay MCP: Deep Technical Context on Demand
The biggest time sink is gathering the technical evidence. You spend minutes trying to correlate an error message with the specific action that triggered it, switching between console logs and user paths.
Now, your agent can run 'list_session_events' on demand. It pulls out every recorded click, input, and technical event, giving developers and support staff a complete chronological timeline that makes finding the root cause fast.
What your AI can actually do with this
Your agent connects directly to OpenReplay so you can analyze user behavior without leaving the chat interface. You tell it what's broken—maybe a button isn't working on mobile, or an error pops up only sometimes—and your agent handles the heavy lifting. It finds the exact session recording and pulls out all the technical details you need.
Whether you’re checking console logs, tracking specific clicks, or verifying if a user even exists in the project, it gets you to the source of truth fast. If your current AI client supports Vinkius, this MCP brings that deep debugging context right into your workflow. This means no more manual searches across different dashboards; you just talk to your agent and get actionable technical data.
019ea637-93b9-7153-b03b-06047cf480d4 Here's how it actually works
The bottom line is you talk to your agent, and it does the repetitive work of navigating OpenReplay's complex session records so you don't have to.
Subscribe to this MCP and enter your OpenReplay API Key.
Your AI client uses the provided credentials to connect directly to the OpenReplay platform.
You prompt your agent with a natural language request, like 'Find the last 5 sessions for John in Project X,' and it returns the necessary data.
Who is this actually for?
This MCP is for technical roles—developers, support engineers, and product managers—who are tired of switching between debugging consoles, log systems, and helpdesk ticket platforms. It gives them the ability to get deep session context without leaving their main chat window.
When a customer reports 'the button is broken,' they use this MCP to find that user's specific session recording and pull out the exact error message or sequence of clicks that caused the failure.
Instead of setting up complex reproduction steps, they ask their agent to fetch technical events and console logs for a given session ID so they can pinpoint where the code failed.
They analyze user journeys by listing sessions filtered by specific User IDs or projects, allowing them to understand how users are actually interacting with new features in the wild.
What Changes When You Connect
You stop manually searching through session lists. Your agent uses 'list_sessions' to quickly pull up the right records, even if you only know a date range or a User ID.
'search_users' lets you correlate support tickets directly with recorded behavior. You don't have to copy an email and paste it into three different systems just to confirm who complained.
When you need technical proof, the 'list_session_events' tool fetches every click, input, and console log for a session. This gives developers immediate context they can't get from simple error messages.
You can immediately narrow down your search scope using 'get_session'. Once you have a specific session ID, your agent pulls the metadata so you know exactly what that recording is about before diving into the events.
Product teams gain deep insights by asking to list projects first. This helps them understand which application environment—main or staging—they need to analyze user flow data for.
See it in action
A customer reports a form submission error on the mobile app.
Instead of asking the customer for screenshots, you prompt your agent using 'list_sessions' and filter by their User ID. You then use 'list_session_events' to pull all technical data from that specific session, pinpointing whether the failure was a JavaScript error or an unexpected API response.
A developer needs to reproduce a rare console bug.
The team knows the user ID but not the session. They first use 'list_projects' to confirm the correct environment, then ask for sessions using 'list_sessions'. Once they find the timeframe, they get the metadata via 'get_session', and finally retrieve all technical events to see the exact sequence of actions that triggered the bug.
The product team needs to analyze feature adoption.
They ask their agent to run a search using 'search_users' for all internal testers. They then use this list of IDs with 'list_sessions' to see if the new dashboard component is being used at all, and what path users take before they drop off.
The support team needs to verify a user account.
Given just an email address from a ticket, you use 'search_users' to confirm if the person exists in your project. This saves time and lets you immediately pivot to checking recent sessions for that verified ID.
The honest tradeoffs
Searching logs manually
Copying a user's name from the helpdesk ticket, then opening the OpenReplay dashboard, typing the email into the search bar, and manually setting date filters in three different tabs.
Your agent handles this. You simply ask your agent to 'search for users using john@example.com'. The tool uses 'search_users' and immediately gives you a list of IDs or sessions you can reference.
Assuming the error is client-side
Seeing an error message like '401 Unauthorized' and spending hours checking local console code, only to realize the failure happened three steps earlier in a different part of the flow.
Don't guess. Use 'list_session_events'. By retrieving all recorded technical events for that session ID, you can see the entire sequence—and find the moment before the 401 error occurred.
Confusing project scope
Trying to analyze a user flow when they might be interacting with both your main web app and an old staging environment, leading to mixed or inaccurate data.
Start by asking the agent to 'list projects'. This gives you a clean overview of all environments. Then, use the specific Project ID in subsequent calls like 'list_sessions' to ensure your data is siloed and accurate.
When It Fits, When It Doesn't
Use this MCP when your core problem is context—you need to know what happened on the screen, not just that something failed. If you only need simple aggregate metrics (e.g., 'how many people used Feature X'), a standard analytics tool will work fine. However, if your pain point is debugging an intermittent bug, or understanding the exact sequence of clicks leading up to a user drop-off, this MCP is necessary. Specifically, use 'list_session_events' when you need technical proof (console logs, inputs). Use 'search_users' when you need to tie a support ticket directly to a person’s identity. Don't rely on it if you just need to know the total count of sessions; first run 'list_projects' or 'list_sessions' to ensure you are scoped correctly.
Questions you might have
How do I use OpenReplay MCP to find sessions for a specific user? +
You first need to confirm the project using 'list_projects'. Then, prompt your agent to use 'list_sessions', making sure you include the User ID and the correct Project ID in your request.
Does OpenReplay MCP help me find technical bugs? +
Yes. The key is the 'list_session_events' tool. It retrieves every technical action, including console logs, for a session, so you can pinpoint exactly what went wrong.
What if I don't know the user ID? +
You can use 'search_users'. This tool lets your agent find users based only on their email address or name within a specified project, giving you the needed ID to continue your debugging.
Which tools in OpenReplay MCP are best for product managers? +
For analyzing user journeys and feature usage, 'list_sessions' combined with 'search_users' is most helpful. It lets you track groups of users to see how they interact over time.
Can OpenReplay MCP tell me the project name? +
Yes. You use the 'list_projects' tool, which provides a list of all associated projects and their unique IDs, helping you scope your investigation correctly.
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