MCP server

Vetted Consumer

io.github.TheBaronofAI/vetted-consumer

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

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

Working at last checkAbout 2,159 tokens per request once connected9 tools

Website

https://vettedconsumer.com/mcp

At a glance

Type: MCP server
Publisher: Not verified
Status: Working at last check
Tools: 9
Token cost: About 2,159 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to Cursor Add to VS Code VS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

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

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.vetted-consumer]
url = "https://vettedconsumer.com/mcp"

Gemini CLI

{"mcpServers":{"vetted-consumer":{"httpUrl":"https://vettedconsumer.com/mcp"}}}

Cursor

{"mcpServers":{"vetted-consumer":{"url":"https://vettedconsumer.com/mcp"}}}

VS Code

{"servers":{"vetted-consumer":{"type":"http","url":"https://vettedconsumer.com/mcp"}}}

Antigravity

agy mcp add vetted-consumer https://vettedconsumer.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"vetted-consumer","server_url":"https://vettedconsumer.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"vetted-consumer","server_url":"https://vettedconsumer.com/mcp"}

Tools

can_i_run_it ~404 tokens
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 ~236 tokens
The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.
compare_hardware ~294 tokens
Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.
cost_compare ~290 tokens
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 ~104 tokens
Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).
list_hardware ~63 tokens
List the machines the tools know about (memory, bandwidth, price, buy link).
list_models ~66 tokens
List the local LLM model classes the tools know about (params, dense/MoE, native context).
recommend_hardware ~294 tokens
Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.
recommend_quant ~408 tokens
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.

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