README.md•6.96 kB
# OpenAI MCP Server
[](https://smithery.ai/server/@thadius83/mcp-server-openai)
Query OpenAI models directly from Claude using MCP protocol. This fork adds support for o3-mini and gpt-4o-mini models with improved message handling.
## Cline Auto Install
```
Set up the MCP server from https://github.com/thadius83/mcp-server-openai.
Use "github.com/thadius83/mcp-server-openai" as the server name in cline_mcp_settings.json.
Analyse the readme and instructions below. Do not create new files in the repo, utilise the findings from pyproject.toml, src/mcp_server_openai/server.py, src/mcp_server_openai/llm.py
Once installed, demonstrate the server's capabilities by using one of its tools.
Installation Steps:
# Clone the repository
git clone https://github.com/thadius83/mcp-server-openai
cd mcp-server-openai
# Install the package
pip install .`
MCP Settings Configuration: The cline_mcp_settings.json should be configured with:
Correct server name format: "github.com/thadius83/mcp-server-openai"
Python module path structure for the server
PYTHONPATH environment variable pointing to the project directory
OpenAI API key passed as a command line argument
Example configuration:
{
"mcpServers": {
"github.com/thadius83/mcp-server-openai": {
"command": "python",
"args": [
"-m",
"src.mcp_server_openai.server",
"--openai-api-key",
"your-openai-api-key"
],
"env": {
"PYTHONPATH": "/path/to/mcp-server-openai"
},
"disabled": false,
"autoApprove": []
}
}
}
Requirements:
Python >= 3.10
OpenAI API key
Dependencies installed via pip (mcp>=0.9.1, openai>=1.0.0, click>=8.0.0, pytest-asyncio)
Available Tools:
Tool Name: ask-openai
Description: Ask OpenAI assistant models a direct question
Models Available:
o3-mini (default)
gpt-4o-mini
Input Schema:
{
"query": "Your question here",
"model": "o3-mini" // optional, defaults to o3-mini
}
```
## Features
- Direct integration with OpenAI's API
- Support for multiple models:
- o3-mini (default): Optimized for concise responses
- gpt-4o-mini: Enhanced model for more detailed responses
- Configurable message formatting
- Error handling and logging
- Simple interface through MCP protocol
## Installation
### Installing via Smithery
To install OpenAI MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@thadius83/mcp-server-openai):
```bash
npx -y @smithery/cli install @thadius83/mcp-server-openai --client claude
```
### Manual Installation
1. **Clone the Repository**:
```bash
git clone https://github.com/thadius83/mcp-server-openai.git
cd mcp-server-openai
# Install dependencies
pip install -e .
```
2. **Configure Claude Desktop**:
Add this server to your existing MCP settings configuration. Note: Keep any existing MCP servers in the configuration - just add this one alongside them.
Location:
- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%/Claude/claude_desktop_config.json`
- Linux: Check your home directory (`~/`) for the default MCP settings location
```json
{
"mcpServers": {
// ... keep your existing MCP servers here ...
"github.com/thadius83/mcp-server-openai": {
"command": "python",
"args": ["-m", "src.mcp_server_openai.server", "--openai-api-key", "your-key-here"],
"env": {
"PYTHONPATH": "/path/to/your/mcp-server-openai"
}
}
}
}
```
3. **Get an OpenAI API Key**:
- Visit [OpenAI's website](https://openai.com)
- Create an account or log in
- Navigate to API settings
- Generate a new API key
- Add the key to your configuration file as shown above
4. **Restart Claude**:
- After updating the configuration, restart Claude for the changes to take effect
## Usage
The server provides a single tool `ask-openai` that can be used to query OpenAI models. You can use it directly in Claude with the use_mcp_tool command:
```xml
<use_mcp_tool>
<server_name>github.com/thadius83/mcp-server-openai</server_name>
<tool_name>ask-openai</tool_name>
<arguments>
{
"query": "What are the key features of Python's asyncio library?",
"model": "o3-mini" // Optional, defaults to o3-mini
}
</arguments>
</use_mcp_tool>
```
### Model Comparison
1. o3-mini (default)
- Best for: Quick, concise answers
- Style: Direct and efficient
- Example response:
```
Python's asyncio provides non-blocking, collaborative multitasking. Key features:
1. Event Loop – Schedules and runs asynchronous tasks
2. Coroutines – Functions you can pause and resume
3. Tasks – Run coroutines concurrently
4. Futures – Represent future results
5. Non-blocking I/O – Efficient handling of I/O operations
```
2. gpt-4o-mini
- Best for: More comprehensive explanations
- Style: Detailed and thorough
- Example response:
```
Python's asyncio library provides a comprehensive framework for asynchronous programming.
It includes an event loop for managing tasks, coroutines for writing non-blocking code,
tasks for concurrent execution, futures for handling future results, and efficient I/O
operations. The library also provides synchronization primitives and high-level APIs
for network programming.
```
### Response Format
The tool returns responses in a standardized format:
```json
{
"content": [
{
"type": "text",
"text": "Response from the model..."
}
]
}
```
## Troubleshooting
1. **Server Not Found**:
- Verify the PYTHONPATH in your configuration points to the correct directory
- Ensure Python and pip are properly installed
- Try running `python -m src.mcp_server_openai.server --openai-api-key your-key-here` directly to check for errors
2. **Authentication Errors**:
- Check that your OpenAI API key is valid
- Ensure the key is correctly passed in the args array
- Verify there are no extra spaces or characters in the key
3. **Model Errors**:
- Confirm you're using supported models (o3-mini or gpt-4o-mini)
- Check your query isn't empty
- Ensure you're not exceeding token limits
## Development
```bash
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest -v test_openai.py -s
```
## Changes from Original
- Added support for o3-mini and gpt-4o-mini models
- Improved message formatting
- Removed temperature parameter for better compatibility
- Updated documentation with detailed usage examples
- Added model comparison and response examples
- Enhanced installation instructions
- Added troubleshooting guide
## License
MIT License
