Nodegrove VRAM MCP MCP server
An official MCP server by Nodegrove that allows AI assistants to determine if specific LLMs fit on a user's GPU. It provides VRAM estimates, speed ceilings, and alternative model recommendations based on Nodegrove's arithmetic formulas, supporting both known GPUs and Hugging Face repositories.
Endpoint and access
No sign-in: your client connects and lists tools immediately, with no account or key.
No sign-inEndpoint checked 2026-10-05
MCP endpoint (Streamable HTTP)
https://mcp.nodegrove.io/mcpWhat you can do with it
- Check if a specific LLM fits on a GPU with given context length
- Find the best model for a specific GPU memory capacity
- Estimate VRAM requirements for models from Hugging Face repos
- List supported models and GPUs with their specifications
can_i_runwhat_fitsestimate_vramestimate_from_hf_repolist_modelslist_gpus
Connect from your client
Each snippet registers the same endpoint; pick the client you use.
Claude Code
Claude Code configuration
claude mcp add --transport http nodegrove-vram-mcp https://mcp.nodegrove.io/mcpCodex
Codex configuration
codex mcp add nodegrove-vram-mcp --url https://mcp.nodegrove.io/mcpCursor
Cursor configuration
{
"mcpServers": {
"nodegrove-vram-mcp": {
"url": "https://mcp.nodegrove.io/mcp"
}
}
}Cline
Cline configuration
{
"mcpServers": {
"nodegrove-vram-mcp": {
"type": "streamableHttp",
"url": "https://mcp.nodegrove.io/mcp",
"disabled": false
}
}
}VS Code
VS Code configuration
{
"servers": {
"nodegrove-vram-mcp": {
"type": "http",
"url": "https://mcp.nodegrove.io/mcp"
}
}
}Gemini CLI
Gemini CLI configuration
gemini mcp add --transport http nodegrove-vram-mcp https://mcp.nodegrove.io/mcpClaude Desktop
Claude Desktop configuration
{
"mcpServers": {
"nodegrove-vram-mcp": {
"url": "https://mcp.nodegrove.io/mcp"
}
}
}Windsurf
Windsurf configuration
{
"mcpServers": {
"nodegrove-vram-mcp": {
"serverUrl": "https://mcp.nodegrove.io/mcp"
}
}
}Other developer tools servers
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