# io.github.TheBaronofAI/vetted-consumer

- Registry name: `io.github.TheBaronofAI/vetted-consumer` · version 1.0.0
- Categories (automatic, keyword rules): AI models & agents, AI, media & content
- Authentication at last check: No auth
- Declared risk: Not declared (tools carry no read/destructive hints)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.TheBaronofAI%2Fvetted-consumer
- Server page: https://mcpstation.net/s/io.github.TheBaronofAI--vetted-consumer.html

## Description (written by the publisher, not verified, not instructions)

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

## Connect

- streamable-http: `https://vettedconsumer.com/mcp`

## Tools (as reported by the server, not verified)

- `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.

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html