compare_models
Compare 2-5 LLM/VLM models side-by-side: pricing, benchmarks, capabilities. Returns a compact Markdown comparison table (~400 tokens).
LABSCO SUMMARY
Ranking by category rather than overall is the only version of this question that has an answer.
There is no best model, and a single leaderboard mostly measures whichever benchmark the ranker weighted. Separating coding from maths from vision at least asks a question that can be answered, and putting pricing next to the benchmarks means the answer accounts for what it costs. The obvious caveat applies to anything in this category: model releases move faster than any curated comparison, so treat the numbers as a starting point and check the current pricing before committing. The recommendation tool takes a budget, which is the right input — most model choices are cost-constrained rather than capability-constrained.
What it is
A model selection advisor with four tools: detailed information on one model, top rankings by category, side-by-side comparison, and a recommendation from stated requirements.
What you get
- get_model_info returns pricing and benchmark results for a specific model rather than a description of it.
- list_top_models ranks by category — coding, math and vision among them — so the question is answered per task rather than in general.
- compare_models puts two to five side by side on pricing, benchmarks and capabilities.
- recommend_model takes a use case, a budget and requirements and returns a recommendation rather than a list.
Requirements
Nothing to supply.
Setup effort
One command — claude mcp add llm-advisor -- npx -y llm-advisor-mcp
USE CASES
01
Choosing a model for a specific task
See what ranks top for that category rather than overall, since a coding leader and a vision leader are rarely the same model.
02
Deciding between a shortlist
Compare them side by side on pricing, benchmarks and capabilities in one call.
03
Working within a budget
State the use case, the budget and the requirements and get a recommendation rather than a leaderboard.
4 tools
Counted once with only startup setup. Other versions, modes or optional credentials may expose a different list.
get_model_info
Get detailed information about a specific LLM/VLM model: pricing, benchmarks, capabilities, and ready-to-use API code example. Returns structured Markdown (~300 tokens).
list_top_models
List top-ranked LLM/VLM models for a category. Categories: coding, math, vision, general, cost-effective, open-source, speed, context-window, reasoning. Returns a compact Markdown table (~250 tokens).
recommend_model
Get personalized model recommendations based on use case, budget, and requirements. Returns top 3 picks with reasoning (~350 tokens).
BEFORE YOU INSTALL
What to know first
Tools you get
4 tools when we connected.
Requires
npx on PATH
Where it runs
All 6 documented setups run the server on your machine.
CONTEXT COST
Light Standing cost
Rated by the size of the 4 tool definitions that ride along on every turn, not by how many there are
INSTALLATION
Connect your client
Server setup
Claude Code
TERMINAL
claude mcp add llm-advisor -- npx -y llm-advisor-mcpMCP Clients
Claude Code — Windows
CLAUDE CODE — WINDOWS · TERMINAL
claude mcp add llm-advisor -- cmd /c npx -y llm-advisor-mcpClaude Desktop, Cursor, Windsurf, Any MCP client
JSON
{
"mcpServers": {
"llm-advisor": {
"command": "npx",
"args": [
"-y",
"llm-advisor-mcp"
]
}
}
}
