{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/12"}],"enrichment":{"capability":"mcp-use provides a Python framework to connect LLMs to Model Context Protocol servers, enabling agents to discover and call tools, clients to access MCP servers directly, and developers to build and deploy MCP servers.","skillfed_tags":["llm-integration","agent-framework","tool-calling"],"use_cases":["Build an AI agent that can call multiple external APIs or services by connecting them as MCP servers.","Create a chatbot that dynamically selects and executes tools from a pool of MCP servers based on user requests.","Develop a custom MCP server to expose internal tools or data sources to LLM-powered applications.","Integrate file system, database, or network tools into an LLM workflow with built-in safety restrictions.","Prototype AI agent logic using the interactive code builder before deploying to production."],"what_it_does":"mcp-use is a Python framework that bridges LLMs and the Model Context Protocol (MCP), a standard for connecting AI models to external tools and data sources. It provides three main components: an MCP Agent that reasons across multiple steps and selects tools to solve problems, an MCP Client for direct programmatic access to MCP servers, and an MCP Server builder for creating and deploying custom servers.\n\nThe package is designed for developers building AI applications that need tool access. It works with langchain-supported LLMs that support tool calling and handles multiple MCP servers simultaneously, allowing agents to dynamically select the appropriate server for a given task. It includes features like tool restrictions for safety, HTTP support for remote servers, and custom agent building via langchain adapters.","worth_installing":"Yes, if you are building LLM-powered applications that need tool access and want a structured framework for MCP integration. The low install friction, active maintenance, permissive license, and support for multiple LLM providers make it a solid choice. The Alpha status and 11 dependencies warrant testing in a non-critical environment first, but the lack of known vulnerabilities and recent release cycle suggest reasonable stability for early adoption."},"id":"mcp-use","links":{"html":"https://skillfed.io/packages/mcp-use","md":"https://skillfed.io/packages/mcp-use.md","pypi":"https://pypi.org/project/mcp-use/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-17","license_spdx":null,"license_treatment":"permissive","name":"mcp-use","python_support":"supports_current","summary":"Full Stack MCP framework for python, build MCP agents, clients, and servers."},"popularity":{"monthly_downloads":420524,"position":6789,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.7.0"}