@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 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

• tokenmark_recommend — { hardware, tasks?, prefer?, limit? } → ranked model + best-config picks with measured tok/s + why.
• tokenmark_configs — { model?, hardware?, limit? } → tracked benchmark configs.
• tokenmark_search — { term } → matching models/configs.

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

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