"A router for MCP (Model Context Protocol) tools" matching MCP servers:

A production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.

A basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.

MCP server for exploring and querying Supabase databases with interactive React widgets for schema browsing, table viewing, and SQL execution.

Enables a Codex orchestrator to obtain a deterministic, local recommendation for a model and reasoning effort for a delegated coding task, without inference calls or API keys.

Enables users to route Codex desktop chats to subscription models or their own OpenAI-compatible providers by adding Base URLs, API keys, and model catalogs from an in-app settings panel. Keeps keys DPAPI-encrypted, supports Responses and Chat Completions with streaming and tool calls, and needs no separate configuration app or Windows autostart.

A Python-based server for managing and analyzing code context for AI-assisted development. Provides real-time code analysis, project structure analysis, dependency tracking, and secure API endpoints.

Routes each prompt to the best-fitting Claude model via a local, zero-cost classifier, exposing a single smart_prompt tool for MCP clients.

A local-first MCP server and CLI that gives coding agents structured project memory, task contracts, context packs, backlog workflows, and verification evidence, storing data in reviewable Markdown/YAML with a fast SQLite index.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

A server built with mcp-framework that allows users to extend Claude's capabilities by adding custom tools that can be used through the Claude Desktop client.

Serves MCP tools and resources over a Streamable HTTP endpoint, letting clients invoke methods such as echo through JSON-RPC 2.0 requests. Its methods are generated from an OpenAPI Specification file and can be customized via environment variables for port and API URL.

An MCP server for integrating AI models with client applications, allowing for structured interactions with APIs using command-line arguments for authentication and configuration.

Enables AI assistants to interact with Square's Connect API through the Model Context Protocol standard, allowing for operations like managing customers, processing payments, and handling inventory.

AIFeed Open Standard. AIFeed Protocol to the building tools section. AIFeed enables web publishers to provide verified, token-efficient content feeds for AI agents.

Enables creating Spotify playlists based on text descriptions by connecting Cursor editor to Spotify's API through OAuth authentication.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

A lazy router for Claude Code skills that exposes a library of skills through search, load, and reindex MCP tools, reducing context usage by only loading skills on demand.

A centralized gateway platform for aggregating and managing multiple Model Context Protocol (MCP) servers through a single Electron-based interface. It provides enterprise-grade security features including policy-based access control, human-in-the-loop approval workflows, and comprehensive audit logging.

A TypeScript wrapper library for the Model Context Protocol SDK that provides a simplified interface for creating MCP servers with tools, resources, and prompts without needing to work directly with the protocol.

A comprehensive demonstration server that provides tools for calculations, weather, and note management alongside an interactive web interface. It showcases how AI assistants can seamlessly interact with external data sources and functions using the Model Context Protocol.

A server that allows AI models to interact with PostgreSQL databases through a standardized protocol, providing database schema information and SQL query execution capabilities.

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

A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.

Enables AI agents and their users to submit, route, and monitor training jobs across free-tier GPU clouds (Kaggle, Colab, Lightning, local MPS) through a local daemon that tracks quota, explains routing decisions, and gates long or secret-reading agent jobs behind human approval.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

Enables repo-scoped expert consultation from Claude Code by compressing difficult questions into structured briefings and routing them through ai-browser-bridge to ChatGPT web, with per-project activation and safeguards.

MCP server for parsing, validating, building and explaining FIX protocol trading messages — offline, no API keys.

This MCP server lets agents route natural-language requests to the best matching workflow or tool using weighted lexical scoring and two-gate abstention. It returns ranked candidates with match evidence or explicitly refuses when confidence or score falls below calibrated thresholds.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

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.

Enables agents to connect through a single gateway that has a decision model pick which MCP tools and playbooks are relevant to each request, so the LLM only sees the few schemas it needs, and to then invoke those tools on the underlying servers. This cuts tool-selection cost and prompt size dramatically when many MCP servers are connected.

Enables Claude Code and Codex Herdr workers to get local, advisory routing decisions by selecting a client, model, effort tier, and worker launch instruction for a stage, and by ranking a short list of bounded next actions. Decisions come from a selectable local backend (Laya or a local Kev model), returning confidence and uncertainty without executing anything or granting permissions.

Enables running a project's agent definitions from .github/agents/ against a model the user explicitly names, instead of inheriting whatever model the IDE session happens to use. It reads the agent file as the system prompt, executes a bounded tool loop against a configurable inference gateway, enforces a tiered model allow-list, and reports which model actually ran.

Provides time intelligence, persistent memory and complete traceability for AI coding agents. Enables sophisticated activity tracking, timezone management, smart reminders, and cross-session continuity with support for both per-project and centralized storage modes.

Enables MCP clients to chat through multiple LLM API keys with automatic rotation and failover, discover free and available models, inspect key health and routing, refresh catalogues, ensure a local proxy, and generate OpenCode/Kiro/skill configuration.

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

A Model Context Protocol server that provides tools to manage Keycloak users and realms, allowing you to create and delete users, list available realms, and view users in specific realms.

A simple MCP server implementation that provides AI models with basic Solana RPC methods and helpful development prompts.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.