Vetted Consumer

A free, hosted MCP server for local-LLM hardware decisions. Ask whether a model fits your GPU, Mac, or mini-PC, which GGUF quant to download, the cheapest machine that runs it, and the buy-vs-rent-vs-API cost, from a maintained catalog of models and machines plus a monthly used-GPU price feed. No install, no API key. Tools: can_i_run_it, recommend_quant, cheapest_hardware_for_model, recommend_hardware, compare_hardware, cost_compare, get_used_gpu_prices, list_models, list_hardware. Works with Claude, Cursor, Cline, and any MCP client.

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接入信息

传输形态: http
鉴权方式: 鉴权未知
端点: https://vetted-consumer--hi-10f9.run.tools

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{
  "mcpServers": {
    "Vetted Consumer": {
      "url": "https://vetted-consumer--hi-10f9.run.tools"
    }
  }
}

能力清单

工具	说明
can_i_run_it	Will a given local LLM run on given hardware? Returns fit, the best quant that fits, theoretical tok/s, and real owner-measured tok/s where available.
recommend_quant	Which GGUF quantization to download for a model on given hardware: the full quant ladder with file size, max context, and tok/s for each, plus the recommended pick.
cheapest_hardware_for_model	The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.
list_models	List the local LLM model classes the tools know about (params, dense/MoE, native context).
list_hardware	List the machines the tools know about (memory, bandwidth, price, buy link).
cost_compare	Buy vs rent vs API cost to run a model locally: monthly/1y/3y totals, break-even months, and the energy cost per 1M tokens. Same math as /cost-calculator/.
recommend_hardware	Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.
get_used_gpu_prices	Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).
compare_hardware	Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.

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