"Control Unity Router Configuration and Management" matching MCP servers:

Enables AI clients to control a Unity Editor with a small, token-efficient six-tool facade while retaining access to the full upstream Unity MCP operation catalog.

A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.

Cost-aware multi-LLM routing MCP server that automatically routes tasks to free models first with fallback to paid, using task difficulty classification.

Enables multiple Claude Code sessions to share a single HTTP MCP endpoint, lazily spawning stdio MCP servers only when their tools are called, reducing idle processes and memory usage.

Enables agents to search a local catalog, load skills, inspect MCP tool schemas, and invoke selected tools through a single unified MCP tool, reducing per-request overhead.

A durable MCP control plane for starting, observing, steering, continuing, cancelling, and handing off long-running coding agents, with bounded MCP calls and persistent worktrees.

Aggregates and routes to hundreds of downstream MCP servers behind a single interface, exposing only five meta-tools and dynamically retrieving the relevant tool for an agent on demand.

Automatically selects the optimal LLM model for each task in Cursor IDE by analyzing query complexity, task type, and applying customizable routing strategies across 17 different AI models.

Enables efficient tool routing and context budgeting for AI agents handling hundreds of MCP tools, with circuit breaker, RBAC, and federation for reliable serving.

Aggregates and routes multiple MCP servers with intelligent tool recommendation and batch parallel execution, enabling unified access and efficient tool usage.

Routes SKILL.md libraries to any MCP client, enabling task matching and skill loading with embedding-based scoring, keyword fallback, and context-window discipline.

This MCP server enables LLM hosts to plan large tasks and delegate subtasks to specialized local CLI agents, such as Codex and Claude Code, using tools like delegate_task and get_agent_roster.

Enables orchestrator agents to route coding tasks to native CLI worker agents via MCP, providing tools for agent discovery, task submission, waiting, inspection, and cancellation.

Enables AI agents to choose the lowest-carbon cloud region for a workload, with tools for ranking regions by carbon intensity and latency, and for finding optimal start times to reduce emissions.

Enables AI coding agents to make fast, zero-output-token decisions by evaluating context, diffs, logs, or options through the OpenRouter Decisions API using TypeSafe Jev, returning calibrated probabilities for binary, categorical, or scoring questions.

Routes your AI tasks to the best available model across 20+ providers — automatically selecting based on task type, budget, and subscription pressure. Supports text, image, video, and audio with built-in cost optimization and fallback chains.

Route prompts intelligently across Claude, Gemini, and GPT-4o, automatically picking the best model for every task while minimizing token cost.

Provides deterministic intent routing and safety gating for multi-agent systems, enforcing P0 critical word detection, mutually exclusive hard rules (MX-1/2/3), and a permission matrix as pure functions via four MCP tools.

An MCP server that routes LLM requests across multiple providers and orchestrates other MCP servers, with a focus on local privacy for embeddings and memory.

MCP server that routes AI chat requests to the best available provider (Anthropic, OpenAI, Groq, etc.) with automatic fallback, budget caps, and model-tier routing.