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openai_mcp_server MCP server

Dockerized MCP server for OpenAI models

Components

Resources

The server implements a simple note storage system with:

  • Custom note:// URI scheme for accessing individual notes
  • Each note resource has a name, description and text/plain mimetype

Prompts

The server provides a single prompt:

  • summarize-notes: Creates summaries of all stored notes
    • Optional "style" argument to control detail level (brief/detailed)
    • Generates prompt combining all current notes with style preference

Tools

The server implements one tool:

  • add-note: Adds a new note to the server
    • Takes "name" and "content" as required string arguments
    • Updates server state and notifies clients of resource changes

Configuration

[TODO: Add configuration details specific to your implementation]

Quickstart

Install

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Servers Configuration ``` "mcpServers": { "openai_mcp_server": { "command": "uv", "args": [ "--directory", "Z:\FUCK", "run", "openai_mcp_server" ] } } ```
Published Servers Configuration ``` "mcpServers": { "openai_mcp_server": { "command": "uvx", "args": [ "openai_mcp_server" ] } } ```

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory Z:\FUCK run openai-mcp-server

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

Building the Docker Image

docker build -t openai-mcp-server .

Running the Docker Container

docker run -d -p 8000:8000 -e OPENAI_API_KEY=your_api_key_here openai-mcp-server

Replace your_api_key_here with your actual OpenAI API key.

Metadata

Release files for openai-mcp-server 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for openai-mcp-server 1.0.0
File Size Uploaded
openai_mcp_server-1.0.0.tar.gz 10.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for openai-mcp-server 1.0.0
File Interpreter ABI Platform
openai_mcp_server-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 15.4 kB

Release files / openai_mcp_server-1.0.0.tar.gz

Download URL openai_mcp_server-1.0.0.tar.gz
Size 10.8 kB
Tags Source
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Uploaded via uv/0.6.12

Release files / openai_mcp_server-1.0.0-py3-none-any.whl

Download URL openai_mcp_server-1.0.0-py3-none-any.whl
Size 4.6 kB
Tags Python 3
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305d768f3e05df95c572a3306001d53aa45989e3ba162dd20d251de3a4b2e3d9
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Uploaded via uv/0.6.12

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This release

1.0.0 This release

2 release files

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