Py Mcp Collection
What is Py Mcp Collection
py-mcp-collection is a repository containing a collection of assorted MCP Servers designed to assist AI Coding Assistants with various functionalities.
Use cases
Use cases include customizing server responses, managing file operations in bulk, and providing documentation references to AI Coding Assistants to improve coding guidance.
How to use
To use py-mcp-collection, you can start by exploring the individual MCP Servers provided in the repository, such as MCP Oops, Filesystem Operations, and Local References. Each server has its own README file with specific instructions.
Key features
Key features include the ability to modify MCP Server behavior with MCP Oops, perform bulk file and folder operations with Filesystem Operations, and reference local files and folders with Local References.
Where to use
py-mcp-collection can be used in software development environments, particularly where AI Coding Assistants are integrated to enhance coding efficiency and best practices.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Py Mcp Collection
py-mcp-collection is a repository containing a collection of assorted MCP Servers designed to assist AI Coding Assistants with various functionalities.
Use cases
Use cases include customizing server responses, managing file operations in bulk, and providing documentation references to AI Coding Assistants to improve coding guidance.
How to use
To use py-mcp-collection, you can start by exploring the individual MCP Servers provided in the repository, such as MCP Oops, Filesystem Operations, and Local References. Each server has its own README file with specific instructions.
Key features
Key features include the ability to modify MCP Server behavior with MCP Oops, perform bulk file and folder operations with Filesystem Operations, and reference local files and folders with Local References.
Where to use
py-mcp-collection can be used in software development environments, particularly where AI Coding Assistants are integrated to enhance coding efficiency and best practices.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
This repository contains a collection of MCP servers that are useful for AI Coding Assistants.
Currently there are three MCP Servers ready to be used:
- 🎤 MCP Oops 🎤
- Filesystem Operations
- Local References
| MCP Server | Why it’s neat | Status |
|---|---|---|
| 💾 Filesystem Operations | Performs bulk file read, preview and search operations and provides code and text summarization options to help find relevant files. | ✅ |
| 📚 Local References | Allows exposing existing documentation in the project as “Best Practices” or “How To” guides / etc to the AI Coding Assistant. | ✅ |
| 🔍 Doc Store Vector Search | Allows storing and searching documents in a vector store. | 🚧 |
| 🎤 MCP Oops | Allows modifying the behavior of someone else’s MCP Server. | 🚧 |
| MCP Libraries | Why it’s neat | Status |
|---|---|---|
| 🔧 MCP Utils | Provides utilities for MCP Servers. | Provides utilities for MCP Servers!! |
MCP Oops
This MCP Oops is a wrapper server that allows you to significantly modify the behavior of an MCP Server. It can be used to limit response sizes, host multiple MCP Servers on a single port, change tool names, descriptions, call pre/post hooks, and more.
To get the started with MCP Oops, see the MCP Oops README.
Filesystem Operations
This MCP Server provides tools for performing bulk file and folder operations. It includes centralized exception handling for filesystem operations.
To get the started with Filesystem Operations, see the Filesystem Operations README.
Local References
This MCP Server provides a way to reference local files and folders in the codebase. This allows you to expose existing documentation in the project as “Best Practices” or “How To” guides / etc to the AI Coding Assistant.
To get the started with Local References, see the Local References README.
There are additional MCP servers under development:
- Doc Store Vector Search
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
