FitLLM

Will this LLM fit on your GPU, multi-GPU rig or Mac?

Connector by fitllm.runOfficial · Domain verified by the MCP Registry

IndexedMITRemote (HTTP)★ 8

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Install

Works with Claude Code, VS Code, Cursor, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install connector/fitllm-run-fitllm

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Remote endpoint

https://fitllm.run/api/mcp Remote (HTTP)

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About

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

Use cases: model-inference

Reviews

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No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this server can do and what it asks for, from its tool list and install config. Checked Oct 25, 2026.

Tools: 3 read · 0 write · 0 deleteRead-only
Secrets: None asked for
Install scripts: Nothing to install (hosted)
Runs as: Hosted (remote endpoint)

Tools by what they do 3

From the running server's own tool list (tools/list) on Oct 25, 2026.

Read 3 · Look things up without changing anything.

check_llm_fit
list_supported
what_fits_on_hardware

Network hosts it talks to 1

fitllm.run · found in remote endpoint, install command

Tools (3)

As the server listed them on Oct 25, 2026. Descriptions are the server’s own words; hidden characters are shown as [U+…].

check_llm_fitCheck if an LLM fits on hardwareread-only
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).
list_supportedList supported models & hardwareread-only
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_hardwareWhat LLMs fit on this hardwareread-only
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.

Signals

Stars: 8
Forks: 2
Open issues: 28
Last commit: Oct 23, 2026 (8 days ago)
Last release: Oct 23, 2026 (8 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Registry name: run.fitllm/fitllm
Version: 1.1.0
Auth: Auth not stated
License: MIT
Repository: github.com/click6067-ship-it/fitllm-engine
Website: fitllm.run
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: Official MCP Registry github-graphql

Rank

of 44,833 in Connectors

Score

0.645

Security 30%not yet
Popularity 25%0.53
Freshness 20%1.00
Rating 15%not yet
Docs 10%0.87

How ranking works →

Grades

Freshness

Active in the last 30 days. Last activity 8 days ago.

–

Security

Security scan: in progress. Grades from our dependency, secret, code and prompt-injection checks appear here once they launch. Until then, check the code before you install.

Indexed

Found automatically from a public source. Not yet claimed by its publisher.

How grades work →

Availability

100% uptime, last 30 days (2 checks)

Last check: 6 days ago
Status: Up
Median response: 405 ms

Up
Up, auth required
Down
Not checked
No data

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Cite this page

FitLLM MCP server. Agent Mart. https://agentmart.dev/connectors/fitllm-run-fitllm (last updated 2026-10-24)