"The Models Resource" matching MCP servers:

Evaluates task suitability for local models before cloud API calls, routing to Ollama or similar to reduce costs.

Routes questions to a council of AI models (local and cloud) and synthesizes their answers in five configurable modes: individual, categorized, deconflicted, pooled, and dialectic.

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

Routes questions to multiple AI models (local and cloud) and synthesizes their answers in individual, categorized, or deconflicted modes.

Delegate tasks from Claude Code to other models (Codex CLI, DeepSeek, OpenRouter, etc.) without leaving the app.

Provides integration with OpenRouter.ai, allowing access to various AI models through a unified interface.

Enables models to discover, inspect, and call tools from thousands of MCP servers on the fly through a single gateway, without pre-configuring each server.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Local MCP server that lets Claude Code delegate bounded, read-only tasks to external AI models (Codex, Grok, local OpenAI-compatible servers) via CLIProxyAPI.

Enables thinking models to extend their reasoning by outsourcing parts of the chain of thought to a non-thinking model via the chat_agent tool, with configurable parameters.

An MCP server that exposes tools for sub-agent style reasoning across multiple LLM providers, enabling delegation of prompts to various models and running critique loops, debates, red-teaming, and answer ranking.

Enables delegating Claude Code subagent tasks to cheaper opencode models, while keeping the main Claude Code session connected directly to Anthropic.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

Plan your projects with The High Council! Several AI models from different labs argue about your idea, then debate on Software Engineering choices. The goal is to get everyone to work together, in harmony and with manners. Effectiveness is unproven, but it is a fun way to spend your tokens!

MCP server for multi-agent AI systems providing mailbox messaging, A2A task delegation, resource coordination, and a web dashboard.

MCP server for interacting with fal.ai models and services. Uses the latest streaming MCP support.

Model Context Protocol (MCP) server implementation that enables Claude Desktop to interact with Google's Gemini AI models.

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

MCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.

An MCP server that queries multiple Ollama models and combines their responses, providing diverse AI perspectives on a single question for more comprehensive answers.