Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.
Connect Remote server
claude mcp add --transport http vetted-consumer https://vettedconsumer.com/mcp
{
"mcpServers": {
"vetted-consumer": {
"url": "https://vettedconsumer.com/mcp"
}
}
}
{
"servers": {
"vetted-consumer": {
"type": "http",
"url": "https://vettedconsumer.com/mcp"
}
}
}
Settings > Connectors > Add custom connector
URL: https://vettedconsumer.com/mcp
Tools 9 found in our last check
can_i_run_itWill 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_quantWhich 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_modelThe cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.
list_modelsList the local LLM model classes the tools know about (params, dense/MoE, native context).
list_hardwareList the machines the tools know about (memory, bandwidth, price, buy link).
cost_compareBuy 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_hardwareRanked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.
get_used_gpu_pricesCurrent typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).
compare_hardwareSide-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.
Details
| Endpoint | https://vettedconsumer.com/mcp (Streamable HTTP) |
| First published | 22 Jun 2026 |
| Last updated | 22 Jun 2026 |
| Registry name | io.github.TheBaronofAI/vetted-consumer |
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