"MEGA" matching MCP servers:

A unified MCP server providing tools for web search, GitHub analysis, document parsing, browser automation, secure code execution, and forum parsing, enabling LLMs to perform a wide range of external tasks through a single backend.

Enables deploying a secure MCP gateway that proxies, sandboxes, and policy-governs third-party MCP servers, with credential vaulting and audited tool access across stdio, SSE, and Streamable HTTP.

Unifies local Agent Skills from DSH, Claude, Codex, Magpie, and shared agent directories behind a single lazy-loading facade, exposing three tools to search, list, and load skills on demand. It keeps system prompts lean by fetching full SKILL.md instructions only when a task needs them, and returns local paths so bundled references, scripts, and assets stay reachable.

Turns any OpenAPI specification into an MCP server exposing three tools to search operations, inspect one operation's parameters and request body, and call it via HTTP. This keeps the tool list small while making every API operation reachable, with auth headers supplied from environment variables and hidden from the agent.

Federates multiple MCP servers into a single endpoint with search, call, and admin tools, plus inbound/outbound OAuth.

Enables users to run queries across multiple AI models in parallel, comparing latency, token speed, and cost, and to integrate this multi-model racing and code review capability into Claude Code, Cursor, and Codex CLI.

A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.

Enables MCP clients to access many upstream MCP servers through two lazy tools that list and call tools, fetching schemas only when needed to reduce per-request schema overhead.

Enables autonomous agents and multi-agent frameworks to discover and execute modular, class-based tools over SSE with a standardized response contract.

A production-grade MCP server that provides a centralized microservice toolkit for LLM agents, enabling web search and extensible tool integration.

AI Agent superpowers with 1 API key - zero auth, always SOTA

A server that transforms a standard Language Model into a dynamic multi-agent system where the model simulates both a Conductor (project manager) and Experts (specialized agents) to tackle complex problems through a collaborative workflow.

A meta API Gateway server that works with the Model Context Protocol (MCP), enabling AI assistants to connect to any API and access real-world data sources through standardized MCP tools.

Enables AI agents to combine ambient multimodal perception, continuous episodic memory, and recency-decay context briefing for fast deterministic decisions and safe tool routing. It integrates with MCP clients to reduce unnecessary frontier LLM calls while enforcing token budgets and local-first memory retention.

Enables personal AI agents to fuse ambient multimodal perception with continuous episodic memory streams, routing routine reflexive actions at low latency while reserving heavier reasoning for ambiguous plans. Memory records apply Ebbinghaus recency decay with contradiction resolution and user-controlled deletion.

Aggregates multiple remote Model Context Protocol endpoints and exposes them through a unified SSE interface, allowing an LLM client to interact with specialized servers without configuration changes.

Enables the deployment of remote Model Context Protocol servers on Cloudflare Workers without authentication using Server-Sent Events. It provides a boilerplate for developers to add custom tools and connect them to clients like Claude Desktop or the Cloudflare AI Playground.

A Model Context Protocol server that wraps multiple backend servers for token-efficient tool discovery via lazy loading. It enables AI models to browse available servers and fetch specific tool schemas on-demand, significantly reducing initial context overhead.

Aggregates tools from multiple MCP servers, generates TypeScript definitions, and executes custom TypeScript scripts to orchestrate cross-server tool calls.