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A guide to advanced Model Context Protocol concepts, including reusable prompts, requests for text generation, resource roots, and communication transports. MCP is a standard for connecting AI assistants with tools and data.
Cursor rule Cursor
A guide to advanced Model Context Protocol concepts, including reusable prompts, requests for text generation, resource roots, and communication transports. MCP is a standard for connecting AI assistants with tools and data.
Cursor rule Cursor
A guide to the core architecture of the Model Context Protocol (MCP), a standard way for AI applications to connect with data sources and tools. It explains hosts, clients, servers, resources, tools, and other protocol concepts.
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A set of guidelines for building MCP clients—programs that connect to MCP servers to discover and use their tools, resources, and prompts.
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A guide to defining and exposing resources in MCP, a standard that lets AI assistants use data from connected servers. It covers resource addresses, content, metadata, permissions, listing, updates, and retrieval.
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A reference guide for building MCP servers, which are programs that let AI clients safely access data and run operations. It covers the Model Context Protocol, a standard way for these programs to communicate.
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A Chinese-language guide to defining and exposing tools through MCP, a standard way for AI clients to discover and call server-provided actions.
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A guide to managing Python dependencies and building packages with uv, a fast tool that installs and resolves Python packages. It focuses especially on projects published to PyPI, the main public index for Python packages.
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A project-structure guide for Python servers that use MCP, a standard for connecting AI assistants to tools. It recommends where to put source code, configuration, dependencies, tests, documentation, and related files.
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A set of coding rules for Python projects, based on Google’s Python Style Guide and common Python practices. It covers formatting, imports, naming, and related project conventions.
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A set of guidelines for writing comments in Python source code. It covers clarity, language, formatting, inline comments, and keeping comments accurate as code changes.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: