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Give your AI assistant real-time LLM/VLM knowledge. Pricing, benchmarks, and recommendations — updated every hour, not every training cycle.
LLMs have knowledge cutoffs. Ask Claude "what's the best coding model right now?" and it cannot answer with current data. This MCP server fixes that by feeding live model intelligence directly into your AI assistant's context window.
- Zero config — No API keys, no registration. One command to install.
- Low token — Compact Markdown tables (~300 tokens), not raw JSON (~3,000 tokens). Your context window matters.
- 5 benchmark sources — SWE-bench, LM Arena Elo, OpenCompass VLM, Aider Polyglot, and OpenRouter pricing merged into one unified view.
Works with Claude (desktop and mobile), Cursor, Windsurf, VS Code, and any MCP-compatible AI app.
Category: Developer Tools
Don't lose this
Three weeks from now, you'll want Daichi-Kudo/llm-advisor-mcp again. Will you remember where to find it?
Save it to your library and the next time you need Daichi-Kudo/llm-advisor-mcp, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. Daichi-Kudo/llm-advisor-mcp. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from awesome:punkpeye/awesome-mcp-servers
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