MCP.Market

TokenMark MCP server

by sypherin·io.github.sypherin/tokenmark-mcp·v0.4.1

Measured local-LLM speeds and model picks for Strix Halo, DGX Spark, Mac and GPU cards.

A92/100grade A
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A92/100

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Adoption
Growing

0 stars477 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

TokenMark tools

No tool declarations could be read from the package source. They show once the server is installed.

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How TokenMark compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
92/100
higher than 90% of 4,460 AI and agents servers
Downloads a week
477
more than 86% of 1,538 AI and agents servers with a package

Release history: 3 versions in the registry since 2026-10-05, latest 2026-10-23, typically one every 13 days.

Install TokenMark in Claude Code, Cursor or VS Code

Runs npx -y @altronis/tokenmark-mcp on your machine. Read the scan report first; the gateway never runs local packages.

claude mcp add tokenmark-mcp -- npx -y @altronis/tokenmark-mcp
Add to Cursor

What the publisher says

From the TokenMark repository's README, as published. We do not edit it. Read it on GitHub

@altronis/tokenmark-mcp

An MCP server that gives Claude (and other agents) real local-LLM benchmark data + hardware-aware model recommendations from TokenMark.

Ask "what should I run on a Strix Halo for coding?" and the agent answers from measured configs (decode tok/s, quant, backend), each with a source link. It never invents numbers.

Add to Claude Code

claude mcp add tokenmark -- npx -y @altronis/tokenmark-mcp

Add to Cline

Cline CLI:

cline mcp add tokenmark --yes -- npx -y @altronis/tokenmark-mcp

Cline in VS Code: add the tokenmark entry from the JSON below to clinemcpsettings.json. Step-by-step notes for agents are in llms-install.md.

Add to any MCP client

Run the server over stdio:

npx -y @altronis/tokenmark-mcp

Or in a client config:

{
  "mcpServers": {
    "tokenmark": {
      "command": "npx",
      "args": ["-y", "@altronis/tokenmark-mcp"]
    }
  }
}

Tools

  • tokenmarkrecommend**: { hardware, tasks?, prefer?, limit? } → ranked model + best-config picks (5 by default, 10 max) with measured tok/s + why.
  • tokenmarkconfigs**: { model?, hardware?, limit? } → tracked benchmark configs, fastest first (25 by default, 50 max; matched gives the full count), with the run mode (speculative: true for MTP/DFlash/draft-model runs).
  • tokenmarkhardware**: { platform? } → the hardware catalogue (Strix Halo, Gorgon Halo, DGX Spark, Mac Max/Ultra). With a platform: chip specs with a source per value, the boxes that ship it, Singapore prices.
  • tokenmarksearch**: { term } → matching models/configs.
  • tokenmarksubmit**: { repo, source?, note? } → queues a GitHub/Hugging Face repo with benchmark numbers for human review.
  • tokenmarksubmissionstatus: { id } → where a submission is.
  • tokenmarksubmitresult: { benchoutput?, pick?, model?, quant?, hardware?, backend?, decodetps?, prefilltps?, ctx?, concurrency?, ..., dryrun? } → sends a speed the user measured, for human review. Pass raw llama-bench or vllm bench serve output as benchoutput, or the fields by hand; fields you pass win over what it read. Sending takes two calls: dryrun: true returns a one-line summary and a confirm code; show the user the summary, and once they agree, call again with the same fields and confirm set to that code. A send without the code, or with fields changed since the dry run, is refused.

Sending measured speeds

tokenmarksubmitresult needs a one-time sign-in on the same machine, in a terminal:

npx @altronis/tokenmark-cli login

Approve the short code at https://tokenmark.app/cli. The sign-in can only send results for review and lasts 90 days; the server reads it on every call, so no restart is needed. Where there is no home directory, set TOKENMARK_TOKEN in the server's environment instead. A sign-in is only sent over https (or plain http to this machine), and every sign-in on the account can be revoked at https://tokenmark.app/cli.

Hardware missing from the catalogue, or a result typed in by hand, can also go through the signed-in form at https://tokenmark.app/submit.

Data is pulled live from https://tokenmark.app (override with TOKENMARK_URL). Zero runtime dependencies.

The same data in your terminal

The CLI lives in cli/ of this repo:

npx @altronis/tokenmark-cli recommend --hardware "Strix Halo" --tasks coding

The files in bin/ are the published builds, made from the TokenMark tracker that runs https://tokenmark.app.

MIT licensed. Data aggregated from public community benchmarks with attribution.

Nothing above is checked by us. What we check is on the safety report.

TokenMark: common questions

Is TokenMark MCP server safe?
Yes, by our scan: it is graded A (92/100). Read the TokenMark safety report
How do I install TokenMark?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does TokenMark need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is TokenMark maintained?
The last commit was 25 days ago (2026-10-09). The latest release is v0.4.1.
What can I use instead of TokenMark?
Servers from other publishers that do the same job: mcptoon MCP server and Guaardvark MCP server.
How does TokenMark compare with other AI and agents MCP servers?
safety score 92/100 (higher than 90% of 4,460 AI and agents servers); downloads a week 477 (more than 86% of 1,538 AI and agents servers with a package). Full comparison.

Alternatives to TokenMark

Same job from other publishers: the closest match first, then the best rated.

  • mcptoon
    MCP tools + agent skills in one zero-dependency CLI: 71,929 -> 581 tokens (-99.2%, measured).
    A
  • Guaardvark
    Local AI studio on your GPU: images, video, music, voice, RAG. Needs the Guaardvark app installed.
    B

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