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Nodegrove VRAM: can I run it?

Can this LLM run on my GPU?

Connector by nodegrove.ioOfficial · Domain verified by the MCP Registry

IndexedMITLocal (stdio)Remote (HTTP)
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Install

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

npx agentmarket install connector/nodegrove-io-vram-mcp

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://mcp.nodegrove.io/mcp Remote (HTTP)

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About

Can this LLM run on my GPU? VRAM, speed ceiling and what fits instead, for any model and GPU.

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
6 read · 0 write · 0 deleteRead-only
Secrets
None asked for
Install scripts
None found
Runs as
Node.js package

Tools by what they do 6

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

Read 6 · Look things up without changing anything.

  • can_i_run
  • estimate_from_hf_repo
  • estimate_vram
  • list_gpus
  • list_models
  • what_fits

Network hosts it talks to 1

  • mcp.nodegrove.io · found in remote endpoint, install command

Tools (6)

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

  • can_i_runCan I run it?read-only

    Can this GPU run this open-weight LLM? Returns fits, tight or no, the memory split (weights, KV cache, overhead), a decode-speed ceiling, the longest context that fits and, on a no, every change that would make it fit: quantisation, KV cache, context, another card or a smaller model. Model: a name or id from list_models, any Hugging Face repo id, or its architecture. GPU: a name or id from list_gpus, or vram_gb for any other card.

  • estimate_from_hf_repoEstimate VRAM from a Hugging Face reporead-only

    Reads any Hugging Face model repo's config.json and parameter count and estimates its memory: the attention layout found (standard, sliding-window, hybrid or latent), how much each 1,000 tokens of context costs, and weights + KV cache + overhead at every quantisation. For models nodegrove.io has not reviewed; anything the reader cannot model is listed in warnings.

  • estimate_vramEstimate VRAMread-only

    How much memory an LLM needs: weights + KV cache + overhead at each quantisation (or one), at a given context, and the smallest common card class that holds each. Model: a name or id from list_models, any Hugging Face repo id, or its architecture (params_b, layers, kv_heads, head_dim).

  • list_gpusList GPUsread-only

    The GPUs and machines nodegrove.io covers: memory, the memory a runtime can use and bandwidth, from the makers' specs, with each one's page.

  • list_modelsList modelsread-only

    The open-weight LLMs nodegrove.io has verified against their config.json (data version 2026-10-16): id, size, attention design, native context, licence, memory at Q4 with 8k context and each model's page.

  • what_fitsWhat fits my GPU?read-only

    Which open-weight LLMs fit this GPU: every model in list_models checked at one quantisation and context, with a recommended everyday model (the biggest class that fits with room for context at conversational speed), the largest that fits, the best at Q8 and the first out of reach. GPU: a name or id from list_gpus, or vram_gb for any other card.

Signals

Stars
0
Forks
0
Open issues
0
Weekly downloads
112
Last commit
Oct 19, 2026 (10 days ago)
Last release
Oct 19, 2026 (10 days ago)
Last package publish
Oct 19, 2026 (10 days ago)

From GitHub (fetched Oct 24, 2026) and the package registry.

Details

Registry name
io.nodegrove/vram-mcp
Version
1.1.4
Auth
Auth not stated
Packages
npm @nodegrove/vram-mcp
License
MIT
Repository
github.com/nodegrove/vram-mcp
Website
nodegrove.io/mcp
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
Official MCP Registrygithub-graphql
Cite this page

Nodegrove VRAM: can I run it? MCP server. Agent Mart. https://agentmart.dev/connectors/nodegrove-io-vram-mcp (last updated 2026-10-24)