For SaaS teams with an MCP server

Product analytics for your MCP server

See which customers get value from your MCP server, where agents get stuck, and which features they're asking for, across Claude, ChatGPT and Cursor.

Early access for teams with a live MCP server. No spam, ever.

Example workspace with illustrative data.

Works wherever your customers use agents

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Any MCP client

Your logs say 200 OK. Your customer says “this is broken.”

Conversations with your MCP server happen in someone else's app, driven by someone else's model. You see tool calls. You don't see whether anyone got what they came for.

Is the MCP server worth it?

Turn MCP usage into ROI you can report

Tie every agent session to the customer account behind it. See which customers rely on your MCP server and what that does for retention, expansion and support load, in numbers leadership already cares about.

Your next roadmap, ranked by demand

Find the features your MCP server is missing

When a customer asks their agent for something your tools can't do, AdapterAI captures it. You get a ranked list of real requests, the accounts asking, and the exact words they used.

  • Spot tools customers need that don't exist yet
  • Catch tools that exist but agents can't find
  • Weigh every request by the accounts and revenue behind it

Improve your MCP server in 4 steps

The same loop product teams run on their web app, now for the agents using your product.

01 · Capture

Hear every customer, in their own words

Listening tools let agents report praise, complaints and confusion as it happens, with sentiment scored and linked to the tool call that caused it.

02 · Diagnose

Find exactly where agents get stuck

Wrong-tool picks, malformed arguments, retry loops and abandoned tasks, grouped by cause and ranked by how many sessions they hurt.

03 · Score

Measure success your way

Plug in decision models like Jev to classify and rate every interaction against rubrics you define, then track them like any other metric.

04 · Improve

Ship fixes and watch them land

Rewrite a tool description, rename a parameter or add a tool, then see whether task success actually went up, per client and per release.

Works with the MCP server you already have

Point AdapterAI at your server. We add a few listening tools alongside yours and leave your tools untouched.

  1. 1

    Connect

    Share your MCP server's URL. No changes to your code.

  2. 2

    Listen

    Agents report feedback and outcomes as customers use your tools.

  3. 3

    Improve

    Insights, missing features and ROI show up in your workspace.

Built for the team that owns your MCP server

You shipped it, customers connected it, and now you're accountable for an experience you can't see.

Product managers

Prove the MCP server is worth investing in, and decide which tools to build, merge or retire next.

The question you're asking

Which customers are getting value from this, and what are they asking for?

Engineers building the server

Find out where agents misuse your tools, fix the names, descriptions and schemas, and confirm the fix worked.

The question you're asking

Did that description change reduce wrong-tool calls, or just move the problem?

Developer experience leads

Make your product feel great in every MCP client, whichever model your customers use.

The question you're asking

Why does this flow work in Claude but keep failing in Cursor?

Become a design partner

We're onboarding a small group of SaaS teams with live MCP servers. Join the waitlist and help shape what we build.

Join the waitlist