mcp server
FitLLM
Will this LLM fit on your GPU, multi-GPU rig or Mac? Exact VRAM & KV-cache math. Read-only.
Description as published by the maintainer. Source
- version 1.0.0
- active
active — Registry entry last updated 2026-07-09.
What this server can do
3 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
check_llm_fit(gpu, model, quant, kv_bits, gpu_count, mac_ram_gb, context_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 full memory breakdown (weights, KV cache, overhead), 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>?". Architecture-aware math (MLA, sliding-window, hybrid attention, MoE) — more accurate than rule-of-thumb estimates. Required: model.
list_supported- List the built-in model names and hardware names this fit-checker knows (for mapping user wording to exact names). Any public HuggingFace model also works via fitllm.run.
what_fits_on_hardware(gpu, gpu_count, mac_ram_gb)- 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.
Last successful function declaration observed on . Source: https://fitllm.run/api/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://fitllm.run/api/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-09 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-07-09 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| mcp tools declared | 3 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | fitllm.run | |
| mcp endpoint status | ok | The server listed 3 functions when asked. | as of probe | fitllm.run |
Where to get it
This record as data
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GET /api/v1/entries/mcp_server.json