MCP server

ComputeSage StackBench Official

com.computesage/stackbench

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

GPU and LLM inference benchmarks, hardware evidence, deployment recommendations, and launch configs.

Website

At a glance

Type

MCP server

Publisher

computesage.com (verified by the MCP Registry)

Status

Working at last check

Tools

5

Token cost

About 2,914 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http stackbench https://mcp.computesage.com/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.stackbench]
url = "https://mcp.computesage.com/mcp"

Gemini CLI

{"mcpServers":{"stackbench":{"httpUrl":"https://mcp.computesage.com/mcp"}}}

Cursor

{"mcpServers":{"stackbench":{"url":"https://mcp.computesage.com/mcp"}}}

VS Code

{"servers":{"stackbench":{"type":"http","url":"https://mcp.computesage.com/mcp"}}}

Antigravity

agy mcp add stackbench https://mcp.computesage.com/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"stackbench","server_url":"https://mcp.computesage.com/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"stackbench","server_url":"https://mcp.computesage.com/mcp"}

Tools

• check_deployment_fit ~254 tokens
  $0.01 USDC on Base mainnet: check model/configuration fit against bounded StackBench capacity evidence.
• generate_launch_config ~596 tokens
  $0.50 USDC: generate deterministic vLLM or llama.cpp launch templates from an exact StackBench recommendation without claiming a launch occurred.
• predict_performance ~526 tokens
  $0.05 USDC: predict configuration throughput, memory, and power from bounded StackBench evidence with confidence, missing metrics, and caveats.
• recommend_deployment ~1414 tokens
  $0.25 USDC: recommend what to buy or run from bounded StackBench fit, performance, confidence, evidence, caveats, and economics only when supported.
• search_evidence ~124 tokens
  $0.00 free search of bounded public StackBench benchmark and failure evidence; use this for evidence-only requests.

Browse

• Calling other AI models

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