A simple Ebay server that uses the official MCP Python SDK to handle protocol communication and provides tools for querying Ebay auctions.

Use the uv tool to create and run a Python project named mcp - server - demo, build a FastMCP server supporting addition functions through the MCP SDK, and configure the client connection.

This project is a server - side implementation based on the Model Context Protocol (MCP) for connecting to the GraphQL API to access policy data. It is built using the Python SDK and GQL library and supports rapid deployment through the uv tool.

The MCP Python SDK is a Python development toolkit that implements the Model Context Protocol (MCP), allowing developers to build standardized MCP servers and clients to provide context data, tools, and interaction templates for LLM applications.

gbox is an open - source self - hosted sandbox project that provides a secure environment for MCP integration and other AI agent use cases. It includes tools such as a terminal, browser, and file editor, supports local task execution and file processing, and provides Python and Typescript SDKs.

A simple Ebay server that uses the MCP Python SDK to handle protocol communication and provides the function of querying Ebay auctions.

Preview version of the MCP Server for Keyfactor Command, built on the Python SDK, supporting certificate management operations such as querying, issuing, and revoking. Currently experimental software not recommended for production use.

A Python-based MCP server implementation that interacts with Notehub projects, devices, and data through the Blues Notehub API and official SDK, providing a standardized external tool integration interface for large language models.

Gossiphs is a zero-configuration, high-performance general code file relationship analysis tool that supports multiple programming languages. It is based on tree-sitter and git analysis, provides support for Python SDK and MCP protocol, and is convenient for integration with AI.

Documentation library for the MCP Python SDK, providing documentation for the Python development toolkit of the Model Context Protocol (MCP), including usage guides and API references for the FastMCP server framework.

The MCP Python SDK is a Python library that implements the Model Context Protocol (MCP), used to standardize the interaction between LLM applications and servers, supporting the exposure and management of resources, tools, and prompts.

This project uses the MCP Python SDK to build a multifunctional server, providing note management, weather query, and news search functions, and supports configuring API keys through the .env file.

This project aims to build an MCP server that interacts with Chrome, including a simple demo version and a robust version based on the Python SDK, used for page screenshot and protocol validation.

The MCP Python SDK is a Python library that implements the Model Context Protocol (MCP) for standardizing the interaction between LLM applications and servers, supporting the exposure and management of resources, tools, and prompts.

The UnifAI SDK now integrates the MCP server and supports TypeScript and Python languages

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

The MCP tutorial introduces how to use an MCP server and client for interaction, including resource discovery, prompt definition, and image return functions.

This guide introduces how to build an MCP server using Python, enabling AI assistants to interact with external tools and data sources through the MCP Python SDK, including installation, quick server setup examples, testing, and deployment considerations.

A model context protocol (MCP) SDK implemented in Python for building standard servers and clients interacting with LLMs

The AWS Boto3 MCP Server is a Python-based MCP service designed to monitor and manage AWS account resources by executing code through the Boto3 client of the AWS Python SDK. The service uses a front - end MCP server and a back - end AWS LightSail container architecture and ensures security by requiring the client to provide valid AWS credentials.

A simple example of an MCP server implemented using the Python MCP SDK and FastMCP

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes server implementations with various functions, such as file system operations, database access, Git management, Slack integration, etc., and supports TypeScript and Python SDKs.

The Bugcrowd MCP Server project provides a Model Context Protocol (MCP) service that exposes all functions of the Bugcrowd REST API as callable tools for use by LLMs and automation processes. This project is implemented using the Python asynchronous MCP SDK and can be integrated with compatible LLM agents such as Claude Desktop.

The Crawl4AI MCP Server is a Python-based web crawler project that integrates Playwright browser automation, the DuckDuckGo search engine, and the MCP protocol SDK for intelligent web data collection.

A simple Ebay server that uses the official MCP Python SDK to handle protocol communication and provides tools for querying Ebay auctions.

This tutorial demonstrates how to create an MCP server using Python and the official Microsoft MCP SDK, showing how to define tool functions that can be used by LLMs (such as models in ChatGPT or Open WebUI).

Minimal Python MCP server implementation based on MCP Python SDK

The OCI Core Services FastMCP Server is a production-level management tool designed specifically for Oracle Cloud Infrastructure. It provides comprehensive compute instance lifecycle management, database operations, and network information query functions. Adopting the LLM-first design concept, it achieves high performance and reliability through the OCI Python SDK.

Documentation project for the MCP server implemented by Python SDK, providing guides for development environment configuration and methods for client integration

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.

This project is a server implementation based on the Model Context Protocol (MCP) for connecting to the GraphQL API to access policy data. It is built using the Python SDK and the GQL library and supports policy queries in the TrueRAG system.

A chart generation server developed based on the MCP Python SDK that can dynamically generate charts based on input data.

A basic MCP client-server implementation project based on the Python SDK, including environment configuration, dependency installation, and running steps.

This project is a development environment integrating the ModelContextProtocol (MCP) SDK and servers. It manages the Python and TypeScript SDKs and officially maintained servers through Git sub - modules, aiming to provide basic context and tool support for developing new MCP servers.

An MCP server for simulated stock trading, supporting stock buying, selling, and analysis functions, built on the MCP Python SDK.

A TAPD server developed based on the MCP Python SDK, which integrates the requirement management function and supports multi - condition query and pagination display.

This is a Python version of the Todoist MCP server, ported from the TypeScript version, providing the same functions through the Python MCP SDK and the Todoist Python API.

This project is a step-by-step guide to building an MCP server using the Python SDK and AlphaVantage API, integrating Claude AI technology.

The OpenAPITools SDK is a Python toolkit that provides developers with a unified interface to manage and execute tools across multiple AI API providers, supporting Anthropic Claude, OpenAI GPT, and the LangChain framework, and two usage modes: local and API.