"Hugging: Exploration and Resources" matching MCP servers:

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

Gitbub mcp

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

Integrates Neovim buffers with Claude, enabling real-time buffer awareness and direct in-editor content updates through MCP resources and tools.

An MCP server that connects LLMs to SQL databases for development assistance, enabling query execution, schema exploration, and data manipulation while providing safety controls against destructive operations.

A template for building Model Context Protocol servers that allow AI assistants to interact with custom data and services through queryable resources and specialized tools.

A production-ready FastMCP server template with modular architecture for building MCP servers with organized tools, resources, and prompts, featuring container support and AI agent documentation system.

An open source Model Context Protocol server for PostgreSQL that provides database health analysis, index tuning, query plan exploration, and safe SQL execution for AI agents throughout the development process.

A TypeScript starter template for building MCP servers with example tools (echo, math operations, time, flight status) and resources (server info, greetings). Provides a modular architecture for easily extending with custom tools and resources.

A comprehensive TypeScript boilerplate MCP server featuring domain-driven design and dynamic component loading. Provides example tools for calculations and text processing, system resources, and writing assistance prompts.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

Enables AI models to interact with AWS Lambda functions via the MCP protocol, allowing access to private resources, real-time data, and custom computation in a secure environment.

Enables code agents to interact with Netlify services through the Model Context Protocol, allowing them to create, build, deploy, and manage Netlify resources using natural language prompts.

A Model Context Protocol server that enables Claude to load CSV files and execute JavaScript data analysis scripts for advanced data exploration and insights generation.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.

A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.

A starter template for building custom MCP servers that can integrate with Claude, Cursor, or other MCP-compatible AI assistants. Provides a clean foundation with TypeScript support, example implementations, and easy installation scripts for quickly creating tools, resources, and prompt templates.

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.

Gives an AI agent its own fleet of disposable Linux microVMs on hardware you control, with tools to spawn, execute commands in, fork from identical disk states, list, and destroy them. Enables safe parallel exploration and cleanup all within an isolated VM boundary.

MCP server for SecretiveShell/Awesome-llms-txt. Add documentation directly into your conversation via MCP resources.

A professional Python framework and template for building robust Model Context Protocol (MCP) servers with modular architecture, enterprise features like authentication and rate limiting, and comprehensive tooling. Provides easy-to-use APIs for registering tools, resources, and prompts with full type safety and multiple transport support.

A dynamic MCP server implementation that automatically loads tools, resources, and prompts from their respective directories, allowing for easy extension and configuration.

A starter template designed to jumpstart the development of Model Context Protocol (MCP) servers using TypeScript. It provides pre-configured examples for creating tools and resources, along with integration guides for MCP clients like Cursor.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK, with examples of tools (calculator, greeting) and resources (server info).

The Fabric-Analytics-MCP server enables AI agents to interact directly with Microsoft Fabric using natural language. It transforms complex data engineering tasks—such as workspace management, data exploration, and job execution—into intuitive, conversational workflows for LLMs like Claude or GitHub

A local MCP gateway that allows AI clients to manage and interact with multiple MCP servers through a single connection, providing token-efficient access to tools and resources.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK, with example implementations of tools (calculator, greeting) and resources (server info).