What tools does the vetted-consumer MCP server provide?

vetted-consumer exposes 9 tools: can_i_run_it, cheapest_hardware_for_model, compare_hardware, cost_compare, get_used_gpu_prices, list_hardware, list_models, recommend_hardware, recommend_quant. This list was returned by the running server when we connected to it.

Does vetted-consumer require an API key?

No. vetted-consumer answered a tools/list request without credentials.

How do I install vetted-consumer?

Run: claude mcp add --transport http vetted-consumer https://vettedconsumer.com/mcp. One-click install links for Cursor and VS Code are also available on the server's page.

Connection check verified live · 26h ago

vetted-consumer

Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.

AI & LLM tooling Memory & knowledge Files & storage

Install

Remote (HTTP)

claude mcp add --transport http vetted-consumer https://vettedconsumer.com/mcp

Tools 9

GitHub stars —

Installs / wk —

Licence —

Transport streamable-http

Last checked 26h ago

Tools & capabilities

9 tools

Read from the running server on 26h ago.

can_i_run_it modelmxfp4contexttotal_bunifiedvram_gb +4

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.

cheapest_hardware_for_model modelmxfp4contexttotal_bactive_b

The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.

compare_hardware modelmxfp4contexttotal_bactive_bhardware* +1

Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.

cost_compare apikwhrenthourstdp_wtokens +2

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/.

get_used_gpu_prices gpu

Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).

list_hardware

List the machines the tools know about (memory, bandwidth, price, buy link).

list_models

List the local LLM model classes the tools know about (params, dense/MoE, native context).

recommend_hardware modelmxfp4budgetcontexttotal_bactive_b +1

Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.

recommend_quant modelmxfp4contexttotal_bunifiedvram_gb +4

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.