"MCP aggregator service or tool" matching MCP servers:

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

MCP server connecting Claude/Cursor to Codex CLI, enabling code analysis via @ file references, multi-turn conversations, sandboxed edits, and structured change mode.

Enables AI assistants to leverage Qwen's code analysis capabilities with large context windows, supporting file/directory analysis, sandbox execution, and multiple approval modes for safe code operations.

Dynamic MCP server for Node.js enabling runtime tool creation, management, and execution in isolated sandboxes (Docker or Node).

A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.

MCP server that integrates Google Gemini CLI with AI assistants, enabling large file analysis and natural language queries without an API key.

A framework to use with AI to easily create a server for any service. Just drop the API Documentation in it and ask to create the MCP.

A Model Context Protocol server that enables AI assistants to interact with Google Gemini CLI, allowing them to leverage Gemini's large token window for analyzing files and codebases using natural language commands.

A starter template for building MCP (Model Context Protocol) servers that integrate with Claude, Cursor, or other MCP-compatible AI assistants. Provides a clean foundation with TypeScript support, example tool implementation, and installation scripts for quick customization.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

A minimal Model Context Protocol server in TypeScript that demonstrates MCP-compliant resources and tools for LLMs, featuring simple resources and a basic tool that echoes messages or returns greetings.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

A command-line tool that transforms any OpenAPI service into a Model Context Protocol (MCP) server, enabling seamless integration with AI agents and tools that support the MCP specification.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

Gives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.

A basic MCP server that implements a calculate tool for arithmetic operations (add, subtract, multiply, divide). It handles requests via stdio.

A tool that generates MCP servers for Smithery with Cursor IDE integration, allowing users to quickly create servers from templates such as Basic, Web Search, or Database interactions.