ai.openmark/openmark · v1.0.0 · productivity
OpenMark is healthy: it completed an MCP handshake in 589 ms and exposes 7 tools.
Benchmark your own prompt on 100+ LLMs with real API calls; pick the cheapest model that passes.
Endpoint: https://openmark.ai/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 7 |
| Latency | 589 ms |
| Last checked (UTC) | 2026-10-18T21:40:31.608Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-18T21:40:31.608Z | Healthy | 589 |
get_task_format | How to write an OpenMark task: the YAML structure, every scoring mode, and tips. Call this before writing a task. |
list_models | Current OpenMark model ids with list prices ($ per 1M tokens). Use these ids in run_benchmark. Append @low, @medium or @high to a reasoning model id to set its reasoning effort. |
prepare_attachments | Get an upload_uid and the exact command to upload images, PDFs or text documents for a task. Upload the files, reference them by file name in each test's attachments list, then pass the upload_uid to run_benchmark. |
run_benchmark | Save a task (YAML, see get_task_format) to the user's OpenMark account and run it on the given models with real API calls. Returns a job_id; poll get_results. Spends the user's credits. |
get_results | Status of a benchmark job, and once completed the ranked results (score, stability, cost per run, latency) plus a recommendation for the chosen objective and quick picks for the others. |
get_account | The user's plan, credit balance and limits, and what a credit pack, Pro or Expert would unlock. Use it before large runs, or when a run is refused for credits or limits. |
watch_task | Watch the task of a completed job: OpenMark re-tests it on new or cheaper models as they ship (no credits used) and emails the user only when one beats the best model of that job. |