MCP server

FitLLM

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

Listed on

First seen 2 Oct 2026. One server, whatever directories list it: each directory listing keeps its own page and history.

Directories

3 via MCP Toplist

Tools

From an anonymous probe

ToolBench grade

Not graded by Arcade

GitHub stars

From MCP Toplist

Tools

Tool	Description	Behaviour
check_llm_fit	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 this whenever a user asks anything like "can I run <model> on my <GPU/Mac>?", "will <model> fit in <N>GB?", or "what do I need to run <model>?". Estimates using curated, config-derived architecture fields (MLA, sliding-window, hybrid attention, MoE modeled).	Read-only
list_supported	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.	Read-only
what_fits_on_hardware	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 naming a model.	Read-only

Directory listings
Directory	Listing	Tier	First seen
Official MCP Registry	FitLLM	-	2 Oct 2026
Smithery	fitllm	-	2 Oct 2026
Glama	Listed there according to MCP Toplist’s dataset; not collected by InvokeRank.
mcp.so	Listed there according to MCP Toplist’s dataset; not collected by InvokeRank.
PulseMCP	Listed there according to MCP Toplist’s dataset; not collected by InvokeRank.