FitLLM is listed as active in the registry but did not answer our last check. It exposes 3 tools. Last commit 28 Oct 2026.
Will this LLM fit on your GPU, multi-GPU rig or Mac? Exact VRAM & KV-cache math. Read-only.
Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 23 August 2026. No other catalogue keeps this.
We read the source, 2 d ago · tools taken from the live server · rules 995398eba69f
Things with no honest explanation: a promise that contradicts the code, code that runs at install time while hiding what it does, data leaving the machine.
execFileSync(process.execPath, [join(dir, 'generate.mjs')], {
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
execFileSync(process.execPath, [join(dir, 'generate.mjs')], {
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
Code changes quietly between releases, and nobody reads the diff of a dependency. We do, on every release — watch FitLLM and you get told the day something new turns up.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 7 min ago.
claude mcp add fitllm --transport http https://fitllm.run/api/mcp
https://fitllm.run/api/mcp
[mcp_servers.fitllm]
url = "https://fitllm.run/api/mcp"
{
"mcpServers": {
"fitllm": {
"url": "https://fitllm.run/api/mcp"
}
}
}
{
"servers": {
"fitllm": {
"type": "http",
"url": "https://fitllm.run/api/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
check_llm_fit
list_supported
what_fits_on_hardware
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://fitllm.run/api/mcp | streamable-http | answering | 50 ms | 7 min ago |
Read-only: which local LLMs a GPU or Mac can run - VRAM fit, tokens/sec, model specs.
Does an LLM fit on your GPU? VRAM, KV cache and GPU count for any Hugging Face model.
Can this LLM run on my GPU? VRAM, speed ceiling and what fits instead, for any model and GPU.
Read-only GPU advisor: model VRAM needs, fit checks and rental prices, with evidence grades.
Read, organise and carefully-gated send for Proton Mail, without your mail leaving this machine.
Read-only Git explainer: what state a repo is in, what an error means, and the exact fix.
What went wrong with your own Ollama calls, in sentences with the fix. Local, read-only.
Read-only ops/health MCP server for a local vLLM instance: health tiers, GPU/VRAM, service status.
Answers built from our own checks of this server.