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Built for the Claude Code community with Claude Code by @mertduzgun

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Rival

nuance-dev/rival-mcp
1STDIOregistry active
Summary

Connects Claude and other MCP clients to rival.tips, a comparison platform for AI models. Exposes four tools: list models with filters for provider, category, or capability; get detailed benchmarks and pricing for a specific model by ID; compare two or three models side by side; and search models by natural language query. No API key needed since it pulls from the public rival.tips dataset covering 60+ models. Useful when you're evaluating which model to use for a task and want benchmark scores, cost breakdowns, or capability matrices without leaving your editor. All read only, returns structured JSON from the rival.tips API.

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RIVAL

rival-mcp

MCP server for querying AI model comparison data from rival.tips

This server lets AI coding assistants — Claude Code, Cursor, Windsurf, and any MCP-compatible client — natively query model benchmarks, pricing, capabilities, and side-by-side comparisons without leaving your editor.

Quick Start

npx rival-mcp

No API key required. All data is served from the public rival.tips API.

Configuration

Claude Code

Add to your .claude/settings.json (project-level) or ~/.claude/settings.json (global):

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

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

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

Cursor

Add to your Cursor MCP settings (.cursor/mcp.json):

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

Windsurf

Add to your Windsurf MCP config:

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

Available Tools

list-models

List all AI models with optional filtering.

Parameters:

ParameterTypeDescription
providerstring (optional)Filter by provider: OpenAI, Anthropic, Google, Meta, Mistral, etc.
categorystring (optional)Filter by category: flagship, reasoning, coding, small, free, image-gen
capabilitystring (optional)Filter by capability: chat, code, vision, image-gen, function-calling
qstring (optional)Free-text search across name, ID, provider, and description

Example prompts:

  • "List all Anthropic models"
  • "Show me free models"
  • "What models support vision?"

get-model

Get detailed information about a specific model — benchmarks, pricing, capabilities, unique features, and provider availability.

Parameters:

ParameterTypeDescription
idstring (required)Model ID, e.g. gpt-4.1, claude-3.7-sonnet, gemini-2.5-pro

Example prompts:

  • "Get details on claude-3.7-sonnet"
  • "What are the benchmarks for gpt-4.1?"

compare-models

Compare 2-3 models side by side — benchmarks, pricing, capabilities, and shared challenges.

Parameters:

ParameterTypeDescription
modelsstring (required)Comma-separated model IDs (2-3). Example: gpt-4.1,claude-3.7-sonnet

Example prompts:

  • "Compare GPT-4.1 vs Claude 3.7 Sonnet"
  • "How does Gemini 2.5 Pro stack up against GPT-4.1 and Claude Sonnet?"

search-models

Search for models by name, description, or capability when you don't know the exact model ID.

Parameters:

ParameterTypeDescription
querystring (required)Search query, e.g. vision, cheap coding, fast reasoning

Example prompts:

  • "Find models good at coding"
  • "Search for cheap reasoning models"

Development

# Install dependencies
npm install

# Run in development mode
npm run dev

# Build for production
npm run build

# Run the built server
npm start

How It Works

This MCP server communicates over stdio (standard input/output) using the Model Context Protocol. When an AI assistant needs model comparison data, it calls the appropriate tool, which fetches data from the rival.tips public API and returns structured JSON.

The server exposes no resources or prompts — only tools. All data is read-only and publicly available.

Data Source

All model data comes from rival.tips, an AI model comparison platform featuring:

  • 60+ AI models with benchmarks, pricing, and capability data
  • Side-by-side comparisons with shared challenge responses
  • Community-driven AI duel voting and rankings
  • Pre-generated showcase responses across coding, creative, and reasoning tasks

License

MIT

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Registryactive
Packagerival-mcp
TransportSTDIO
UpdatedFeb 5, 2026
View on GitHub