MCP server

FitLLM Official

run.fitllm/fitllm

Checked 28 Oct 2026, 09:03 UTC · Connected to it and listed its tools

Will this LLM fit on your GPU, multi-GPU rig or Mac? Exact VRAM & KV-cache math. Read-only.

Working at last checkVerified publisher: fitllm.runAbout 1,040 tokens per request once connected3 tools

https://fitllm.run/api/mcp

At a glance

Type: MCP server
Publisher: fitllm.run (verified by the MCP Registry)
Status: Working at last check
Tools: 3
Token cost: About 1,040 tokens per request
Sets up in: Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
Last checked: 28 Oct 2026, 09:03 UTC

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 fitllm https://fitllm.run/api/mcp

Claude Desktop

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

Codex (config.toml)

[mcp_servers.fitllm]
url = "https://fitllm.run/api/mcp"

Gemini CLI

{"mcpServers":{"fitllm":{"httpUrl":"https://fitllm.run/api/mcp"}}}

Cursor

{"mcpServers":{"fitllm":{"url":"https://fitllm.run/api/mcp"}}}

VS Code

{"servers":{"fitllm":{"type":"http","url":"https://fitllm.run/api/mcp"}}}

Antigravity

agy mcp add fitllm https://fitllm.run/api/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":"fitllm","server_url":"https://fitllm.run/api/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"fitllm","server_url":"https://fitllm.run/api/mcp"}

check_llm_fit ~674 tokens
Check whether a specific local LLM fits in the memory of a specific GPU or Apple Silicon Mac. Returns fits/tight/won't-fit verdict with the memory breakdown (weights, KV cache, linear-attention state when present, runtime overhead, reserve), max context, and a concrete fix if it doesn't fit. Use thi
list_supported ~110 tokens
List the built-in model names and hardware names this fit-checker knows (for mapping user wording to exact names). Standard text-only HuggingFace transformer configs can also be checked via fitllm.run; unsupported architectures are rejected.
what_fits_on_hardware ~256 tokens
Rank which popular local LLMs fit on a given GPU or Apple Silicon Mac (at ~4-bit quantization, 8K context) — models that fit come first, biggest first, with max context each. Use when a user asks "what can I run on my <GPU/Mac/N GB>?", "best local model for my machine?", or gives hardware without na

MarvinLabs vram_fit
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Nodegrove VRAM: can I run it?
Can this LLM run on my GPU? VRAM, speed ceiling and what fits instead, for any model and GPU.
compute.pangle.online — GPU rental market
Live GPU rental market: 2,500+ offers across a dozen provider feeds. History, watches, limit orders.
Retirecrunch Calculators
FIRE & retirement calculators + a multi-currency portfolio rebalancer (exact buy/sell trades).
Hugging Bay
Open model files with recorded SHA-256 and licence labels. Ask for what's missing.
AirTreks MCP
Multi-city flight routing intelligence — plan RTW trips, validate alliances, get carrier picks.
MakerPortal compute
Deterministic engineering solvers: biquad filter design, room eigenmodes, LLM VRAM fit.
MarketAIVerse
A benchmarked market for AI agents: what runs on your GPU, trust checks, encrypted agent rooms.

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