bots.st/openmark

OpenMark

Benchmark prompts via real API calls

2668 ms

answered our call 8 Nov, 02:48 UTC

State: Answered
Protocol: MCP 2025-06-18
Tools listed: 10
Answered: 3 of the last 3 calls

How to reach it

MCP, HTTPhttps://openmark.ai/mcpNeeds header Authorization

What it can do

Tool	What it says it does
`estimate_cost`	Credits a run_benchmark call would use, before spending anything: the expected total, the split per model, the balance needed to start, the worst case, and the user's balance. Same inputs and run settings as run_benchmark. Use it to drop an expensive model, or to compare settings (e.g…
`export_openclaw_csv`	A completed job's results as the CSV the OpenMark Router plugin for OpenClaw reads (the same file as the app's Export > OpenClaw). Save it in the plugin's benchmarks folder, by default ~/.openclaw/workspace/plugins/openmark-router/benchmarks/, and OpenClaw routes this kind of task to the benchmark…
`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.
`get_results`	Status of a benchmark job, and once completed the ranked results (score, stability, cost per run, latency), the tests each model missed with its answer, a recommendation for the chosen objective and quick picks for the others.
`get_task_format`	How to write an OpenMark task: the YAML structure, all 18 scoring modes, and tips. Call this before writing a task. Pass a topic for the full detail on one subject (the app's Task Guide): fields, scoring, composite, chaining, documents, examples, best_practices, or a scoring mode name.
`list_models`	Current OpenMark model ids with list prices ($ per 1M tokens), as text and as a structured list. 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 a one-hour upload link (no API key needed) for images, PDFs or text documents, with the exact curl command. Upload the files, reference them by file name in each test's attachments list, then pass the upload_uid to estimate_cost / 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 and the expected cost; poll get_results. Spends the user's credits; pass max_credits to only start within a budget. Optional run settings match the app's…
`validate_task`	Check a task YAML the way OpenMark will before running it: structure, scoring settings, and the test limit of the user's plan. Free, saves nothing. Returns the problems to fix and warnings worth a look.
`watch_task`	Watch the task of a completed job: when new or cheaper models ship, OpenMark re-tests up to 4 of them next to the user's pick and emails the user only when one beats it. Each check uses the user's credits at the normal rate.

In its maker's words

Benchmark your own prompt on 100+ LLMs with real API calls; pick the cheapest model that passes.

Website: openmark.ai/mcp
Publisher: openmark.ai
Listed from: the official MCP Registry as ai.openmark/openmark
Version: 1.0.0, updated 18 Oct 2026
Kinds of work: AI models and agent tools, Finance and markets

The domain it lives on

openmark.ai: registered 19 Oct 2025 (1 year ago), at GoDaddy.com, LLC, its home page is a working site

From our own crawl of domain names: registry records and the home page as our crawler last saw it.

Every call we made

When	What happened	Time
8 Nov, 02:48 UTC	Answered	2668 ms
7 Nov, 23:29 UTC	Answered	2528 ms
7 Nov, 21:50 UTC	Answered	1022 ms

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