Llm Advisor MCP Server

MCP server for LLM/VLM model selection — compare 300+ models with real-time benchmarks, pricing, and personalized recommendations. No API key

Local serverstdioPython

What is the Llm Advisor MCP MCP server?

MCP server for LLM/VLM model selection — compare 300+ models with real-time benchmarks, pricing, and personalized recommendations. No API key required. That is what the llm advisor mcp mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

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.

The tools it exposes

The server publishes 7 tools. What each one is for:

  • get_model_info — Detailed specs for a specific model: pricing, benchmarks, percentile ranks, capabilities, and a ready-to-use API code example
  • Pricing — The Pricing tool exposed by this server
  • Benchmarks — The Benchmarks tool exposed by this server
  • list_top_models — Top-ranked models for a category. Includes release dates for freshness awareness
  • compare_models — Side-by-side comparison for 2-5 models. Best values are bolded automatically. Includes a Released row so you can spot outdated models at a glance
  • recommend_model — Personalized top-3 recommendations. Scores combine weighted benchmarks, pricing, capability bonuses, and a freshness bonus (+3 points for models
  • Contributing — 1. Fork the repository 2. Create a feature branch 3. Add tests for new functionality 4. Run npm test to verify all 51 tests pass 5. Submit a pull

Getting it running

Installation goes through your MCP client rather than a global install: point it at llm-advisor-mcp on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

What it needs from you

Configuration is passed through the environment: OPENROUTER_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

How it compares

Plenty of developer tooling servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Llm Advisor MCP's toolset — get_model_info, Pricing, Benchmarks and 4 more — is a fair guide to whether it matches your workflow. It is maintained by daichi-kudo; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Available tools

ToolWhat it does
get_model_infoDetailed specs for a specific model: pricing, benchmarks, percentile ranks, capabilities, and a ready-to-use API code example.
PricingThe Pricing tool exposed by this server.
BenchmarksThe Benchmarks tool exposed by this server.
list_top_modelsTop-ranked models for a category. Includes release dates for freshness awareness.
compare_modelsSide-by-side comparison for 2-5 models. Best values are **bolded** automatically. Includes a Released row so you can spot outdated models at a glance.
recommend_modelPersonalized top-3 recommendations. Scores combine weighted benchmarks, pricing, capability bonuses, and a freshness bonus (+3 points for models released within 3 months, +1 within 6 months).
Contributing1. Fork the repository 2. Create a feature branch 3. Add tests for new functionality 4. Run npm test to verify all 51 tests pass 5. Submit a pull request

How to install the Llm Advisor MCP MCP server

{
  "mcpServers": {
    "llm-advisor": {
      "command": "npx",
      "args": ["-y", "llm-advisor-mcp"]
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

VariableDescriptionRequired
OPENROUTER_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Llm Advisor MCP to get model info.
  • Use Llm Advisor MCP to Pricing.
  • Use Llm Advisor MCP to Benchmarks.

Frequently asked questions

It connects Llm Advisor MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 7 tools (get_model_info, Pricing, Benchmarks, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Llm Advisor MCP directly.