Developer tools and code
vram-mcp
vram-mcp was answering at the last check. Checked on 2026-10-04 (daily check).
Can this LLM run on my GPU? VRAM, speed ceiling and what fits instead, for any model and GPU.
Agents use servers like this to work with code, issues, builds and databases.
5 read-only0 change data1 high risk
https://mcp.nodegrove.io/mcp
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Tools
6 tools: 5 read-only, 0 change data, 1 high risk (delete, pay, send or run code).
- read-only
- Only reads or looks things up. Safe for an agent to call on its own.
- changes data
- Creates, edits or sends something. Worth a person's approval the first time.
- high risk
- Can delete, pay, send on your behalf or run code. Hard or impossible to undo.
Connecting costs an agent about 2,854 tokens of tool definitions and a 428 ms handshake.
- high risk
can_i_runCan 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 nam... - read-only
what_fitsWhich 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 ... - read-only
estimate_vramHow 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). - read-only
estimate_from_hf_repoReads 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 ... - read-only
list_modelsThe open-weight LLMs nodegrove.io has verified against their config.json (data version 2026-09-25): id, size, attention design, native context, licence, memory at Q4 with 8k context and each model's page. - read-only
list_gpusThe GPUs and machines nodegrove.io covers: memory, the memory a runtime can use and bandwidth, from the makers' specs, with each one's page.
Levels are automated estimates from each tool's public name, description and annotations, and can be wrong. Descriptions as the server publishes them.
Trust and supply chain
No owner has verified this server yet.
Ships as the npm package @nodegrove/vram-mcp. No OSV advisory for that version (checked 2026-10-04).
No tool change since tracking began on 2026-10-04.
Status
Newest check: answered with tools, from the daily check, 2026-10-04, 428 ms.
From one check a day over the last 1 day. Servers whose owner verified them are checked every 5 minutes. Sign-in and payment answers count as up.
Last 30 days
2026-09-052026-10-04
answered with toolssign-in or payment askednot answeringnot checked
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