OpenRouter MCP Server

OpenRouter MCP Server

An MCP server for discovering and querying over 300 AI models available on OpenRouter. It enables users to list, search, filter, compare, and get detailed information about models with pricing, context limits, and capabilities.

Category
访问服务器

README

OpenRouter MCP Server

MCP (Model Context Protocol) server for discovering and querying 300+ AI models available on OpenRouter.

Features

  • List models — Browse all available models with pricing, context limits, and capabilities
  • Search & filter — Find models by provider, price, context length, features (tools, vision, etc.)
  • Compare models — Side-by-side comparison of multiple models
  • Get details — Full metadata for any specific model
  • Cached responses — 5-minute cache to reduce API calls

Installation

pip install openrouter-mcp

Usage

With OpenClaw

Add to your openclaw.json MCP servers config:

{
  "mcp": {
    "servers": {
      "openrouter-models": {
        "command": "openrouter-mcp",
        "env": {
          "OPENROUTER_API_KEY": "your-api-key"
        }
      }
    }
  }
}

Then restart the gateway. Agents can now use the MCP tools to query OpenRouter models.

Note: OPENROUTER_API_KEY is optional but recommended for higher rate limits (200 req/min vs 20 req/min). Get your key at: https://openrouter.ai/keys

Example agent usage:

# Agent can now call MCP tools like:
list_models(sort_by="context_length")
search_models(query="claude", max_input_price=5.0)
get_model(model_id="anthropic/claude-sonnet-4.6")
compare_models(model_ids="qwen/qwen3.6-plus,anthropic/claude-sonnet-4.6")

Standalone (stdio)

export OPENROUTER_API_KEY=your-key
python -m openrouter_mcp.server

Available Tools

Tool Description
list_models List all models with optional modality filter and sorting
get_model Get detailed info for a specific model by ID
search_models Search and filter models by query, provider, price, context, features
compare_models Compare multiple models side by side
refresh_cache Force refresh the model cache from OpenRouter API

Examples

List models sorted by context length

{
  "name": "list_models",
  "arguments": {
    "modality": "text",
    "sort_by": "context_length"
  }
}

Search for Claude models under $5/1M tokens

{
  "name": "search_models",
  "arguments": {
    "query": "claude",
    "provider": "anthropic",
    "max_input_price": 5.0,
    "requires_tools": true
  }
}

Compare 3 models

{
  "name": "compare_models",
  "arguments": {
    "model_ids": "anthropic/claude-sonnet-4.6,qwen/qwen3.6-plus,openai/gpt-5.4"
  }
}

Get model details

{
  "name": "get_model",
  "arguments": {
    "model_id": "anthropic/claude-sonnet-4.6"
  }
}

API Reference

list_models(modality, sort_by)

  • modality (str, default: "text"): Filter by output type. Options: text, image, audio, embeddings, all
  • sort_by (str, default: "name"): Sort by: name, created, price, context_length

get_model(model_id)

  • model_id (str, required): Model slug, e.g. anthropic/claude-sonnet-4.6

search_models(query, provider, max_input_price, min_context, requires_tools, requires_vision, free_only)

  • query (str): Free-text search in model name/id/description
  • provider (str): Filter by provider (e.g. anthropic, google, openai)
  • max_input_price (float): Max input price per 1M tokens (0 = no limit)
  • min_context (int): Minimum context window size
  • requires_tools (bool): Only models supporting tool calling
  • requires_vision (bool): Only models with vision/image input
  • free_only (bool): Only free models

compare_models(model_ids)

  • model_ids (str, required): Comma-separated list of model IDs

refresh_cache()

Force refresh the model cache from OpenRouter API.

Rate Limits

  • Without API key: 20 requests/minute
  • With API key: 200 requests/minute
  • Model data is cached for 5 minutes

Get your API key at: https://openrouter.ai/keys

License

MIT

Contributing

Contributions welcome! Please open an issue or PR on GitHub.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选