# vetted-consumer MCP server

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

## Links
- Registry page: https://www.getdrio.com/mcp/io-github-thebaronofai-vetted-consumer
- Website: https://vettedconsumer.com

## Install
- Endpoint: https://vettedconsumer.com/mcp
- Auth: Not captured

## Setup notes
- Remote endpoint: https://vettedconsumer.com/mcp

## Tools
- can_i_run_it (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. Endpoint: https://vettedconsumer.com/mcp
- recommend_quant (Recommend a 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. Endpoint: https://vettedconsumer.com/mcp
- cheapest_hardware_for_model (Cheapest hardware for a model) - The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context. Endpoint: https://vettedconsumer.com/mcp
- list_models (List models) - List the local LLM model classes the tools know about (params, dense/MoE, native context). Endpoint: https://vettedconsumer.com/mcp
- list_hardware (List hardware) - List the machines the tools know about (memory, bandwidth, price, buy link). Endpoint: https://vettedconsumer.com/mcp
- cost_compare (Cost: buy vs rent vs API) - 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/. Endpoint: https://vettedconsumer.com/mcp
- recommend_hardware (Recommend hardware) - Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap. Endpoint: https://vettedconsumer.com/mcp
- get_used_gpu_prices (Used GPU prices) - Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly). Endpoint: https://vettedconsumer.com/mcp
- compare_hardware (Compare hardware) - Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines. Endpoint: https://vettedconsumer.com/mcp

## Resources
Not captured

## Prompts
Not captured

## Metadata
- Owner: io.github.TheBaronofAI
- Version: 1.0.0
- Runtime: Streamable Http
- Transports: HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Jun 22, 2026
- Source: https://registry.modelcontextprotocol.io