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MCP live MCP 2025-11-25 http

fitllm

click6067/fitllm

Architecture-aware, read-only LLM fit checks for GPUs, multi-GPU rigs, and Apple Silicon Macs, with full memory breakdowns and no login.

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Watch this dependency Share evidence report
Uptime
100.0%
5 direct probes · 30d
Response
1071ms
last probe
Tools
3
callable
Resources
4
readable
Prompts
0
available
Primary URL
https://fitllm.run/api/mcp
Score: 100/100
Handshake verified by our own probe.
pass Answers the MCP handshake 50/50
The handshake and the list calls succeeded on the primary URL.
pass Lists tools, resources or prompts 30/30
3 tools, 4 resources, 0 prompts returned.
pass 3 or more catalogue items 10/10
7 items in total; 3 or more earns these points.
pass Describes itself 10/10
136 characters; more than 30 earns these points.

Tools · 3

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 …

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 "wha…

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…

Resources · 4

models

Built-in local LLM catalog with the architecture fields the fit engine uses (layers, KV heads/dims, sliding window, MLA, hybrid attention, MoE). JSON.

fitllm://models
hardware

GPUs (VRAM, bandwidth, source-cited) and Apple Silicon chips (unified memory tiers) known to the engine. JSON.

fitllm://hardware
census

Model × device × quant verdicts computed by the engine — starter matrix inline; full CSV/JSON at fitllm.run/data. CC0 data.

fitllm://census
engine

The open MIT calculation engine behind every verdict: source, npm package, conformance vectors, versions. Agents may fetch and run it directly.

fitllm://engine

How to use

Claude Desktop or claude.ai: add a custom connector (Customize → Connectors; on Team and Enterprise plans an owner adds it under Organization settings → Connectors) with this server URL: https://fitllm.run/api/mcp

Cursor or Cline: add to your MCP config:

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