Remote MCP server to run your Atako AI agents: chat, projects, files, integrations and channels.
- Passed: Handshake
- Passed: Tools listed
- Passed: Updated recently
Median latency 132 ms · Last checked
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Evidence for your next connection.
Independent measurements of remote MCP servers. Every observation has a timestamp.
Read-only probesMCP server · Code & DevOps
AI agents use your app like your users, in real browsers, and report what is broken or confusing.
1 failed · 8 not measured
Median of successful probes over 7 days
Share of countable probes over 30 days, including daily rollups. Auth challenges are excluded.
Tool definitions returned by this server
Independent monitoring
Outdated check
Last connection measurement is over 24 hours old. Current availability is unknown.
Last checked| Test area | Passed | Failed | Unmeasured |
|---|---|---|---|
ConnectionCan a client connect and discover tools? | 5 | 0 | 0 |
Reliability & speedDoes it respond consistently and quickly? | 0 | 0 | 4 |
Access & authenticationWhat is required to use this server? | 1 | 0 | 2 |
Tool qualityAre the tool definitions usable by an agent? | 3 | 1 | 0 |
Publisher identityCan the publisher be traced to its source? | 4 | 0 | 2 |
Unmeasured means there is not enough evidence to decide. How these checks work
Start using Mimiq: AI agents use your app like your users and find what breaks
Choose your client, copy the configuration, then enable the server in your client’s MCP settings.
Run this command in your terminal, then restart Claude Code.
Claude Code
claude mcp add --transport http mimiq-ai-agents-use-your-app-like-your-users-and-find-what-breaks https://mcp.mimiqai.com/mcpCapabilities
Show a saved Mimiq run: where it stands while it runs (it waits up to 40 seconds for it to end), then what the agents hit, where each stopped and why, and a link to the full report. Use the session ID from an earlier run or a report URL. Reads your account only and spends no credits.
DiscoveredUse this after you build or change anything a user goes through (signup, onboarding, checkout, settings, a new feature), on the preview or staging URL, and again after each fix. AI agents, each acting as one of the app's users, open it in their own real browser and try the task by clicking, typing and filling in forms (they get a working inbox for verification codes). They report what was broken, what did nothing, where they got stuck or gave up and why, with the step and a screenshot, and the problems ranked by how many agents hit them. Pass the URL and, as goal, the task a user would try in plain words. For a protected preview or pages behind a sign-in, pass access (a Vercel bypass secret, a username and password, or a test account). Each agent keeps going until it finishes the task or gets stuck, so a run takes a few minutes, longer for a long task; each agent uses 5 credits. This call answers within a minute with status still_running, a session_id and a report link while the run goes on: call mimiq.show_report with the session_id until it is finished (if it returns a review, handle that audience warning as below). The same call made again joins that run and uses no more credits. It starts right away and the result includes the audience summary, examples and fit. If the recruited crowd is not the requested audience (more than 1 in 5 wrong) or the page could not be read to check its market, the result is an audience_review instead: show the warning, then continue with review_id, confirm_audience and audience_fit_acknowledged, or recruit again with audience_correction.
DiscoveredRecent measurements
| Checked | Result | Response | Tools |
|---|---|---|---|
| Connected | 343 ms | 2 |