OpenRouter Zero MCP
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Alternatives to OpenRouter Zero MCP
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Related Servers
- AlicenseAqualityDmaintenanceProvides integration with OpenRouter.ai, allowing access to various AI models through a unified interface.4156 npm64Apache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables Claude to invoke third-party models from OpenRouter as tools mid-conversation, including sticky multi-model chat history and model discovery.2 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables chat and image analysis through OpenRouter.ai models. Supports text chat, image generation, and analysis with multiple images and custom questions.721 npmApache 2.0
- FlicenseNot gradedqualityNot gradedmaintenanceGives Claude Desktop access to multiple AI models (Gemini, OpenAI, OpenRouter, Ollama) for enhanced development capabilities including extended reasoning, collaborative development, code review, debugging, and large context analysis with conversation threading.18 npm1-
- AlicenseAqualityCmaintenanceLets Claude Code delegate tasks to OpenRouter-backed Claude Code sessions in isolated child processes, keeping Anthropic and OpenRouter credentials separate. It adds a model catalog, per-job cost tracking, and API-key management for running tasks on 400+ OpenRouter models.729 npmMIT
- AlicenseAqualityBmaintenanceEnables calling 48+ LLMs, image, and video models through Routara's API from Cursor, Claude Desktop, Windsurf, and other MCP clients. Supports chat completions, image generation, and video generation with a single API key.520 npm1MIT
TDQS
Scored across 4 tools
Each tool targets a clearly distinct area: chat inference, account credits, model listing, and API key management. There is no meaningful overlap or ambiguity in intent.
All tools share the openrouter_ prefix and snake_case format, which is highly consistent. The only minor deviation is openrouter_chat_completion, which is noun-based rather than verb_noun like the other three.
Four well-scoped tools cleanly cover the OpenRouter integration surface without redundancy. Each tool earns its place for a focused MCP server.
Core workflows are covered: inference, model discovery, credits, and key lifecycle. Minor gaps exist around richer generation options (e.g. embeddings, streaming controls, per-model usage), but agents can work around them.