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OpenAI MCP Server

by thadius83
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Python
Remote
MIT License
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OpenAI MCP 服务器

铁匠徽章

使用 MCP 协议直接从 Claude 查询 OpenAI 模型。此分支添加了对 o3-mini 和 gpt-4o-mini 模型的支持，并改进了消息处理。

Cline自动安装

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 }

Related MCP server: MCP OpenAI Server

特征

  • 与 OpenAI 的 API 直接集成

  • 支持多种模型：

    • o3-mini（默认）：针对简洁响应进行了优化

    • GPT-4O-mini：增强模型，可提供更详细的响应

  • 可配置的消息格式

  • 错误处理和日志记录

  • 通过 MCP 协议实现简单的接口

安装

通过 Smithery 安装

要通过Smithery自动为 Claude Desktop 安装 OpenAI MCP 服务器：

npx -y @smithery/cli install @thadius83/mcp-server-openai --client claude

手动安装

  1. 克隆存储库：

git clone https://github.com/thadius83/mcp-server-openai.git cd mcp-server-openai # Install dependencies pip install -e .

  1. 配置Claude桌面：

将此服务器添加到您现有的 MCP 设置配置中。注意：请保留配置中现有的 MCP 服务器 - 只需将此服务器添加到它们旁边即可。

地点：

  • macOS： ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows： %APPDATA%/Claude/claude_desktop_config.json

  • Linux：检查你的主目录（ ~/ ）以获取默认的 MCP 设置位置

{ "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" } } } }

  1. 获取 OpenAI API 密钥：

    • 访问OpenAI 的网站

    • 创建账户或登录

    • 导航至 API 设置

    • 生成新的 API 密钥

    • 将密钥添加到您的配置文件中，如上所示

  2. 重启克劳德：

    • 更新配置后，重新启动 Claude 以使更改生效

用法

该服务器提供了一个单独的工具ask-openai ，可用于查询 OpenAI 模型。你可以直接在 Claude 中使用 use_mcp_tool 命令来使用它：

<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>

模型比较

  1. o3-mini（默认）

    • 最适合：快速、简洁的答案

    • 风格：直接、高效

    • 响应示例：

      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-迷你

    • 最适合：更全面的解释

    • 风格：细致、透彻

    • 响应示例：

      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.

响应格式

该工具以标准化格式返回响应：

{ "content": [ { "type": "text", "text": "Response from the model..." } ] }

故障排除

  1. 未找到服务器：

    • 验证配置中的 PYTHONPATH 指向正确的目录

    • 确保 Python 和 pip 已正确安装

    • 尝试直接运行python -m src.mcp_server_openai.server --openai-api-key your-key-here来检查错误

  2. 身份验证错误：

    • 检查您的 OpenAI API 密钥是否有效

    • 确保密钥在 args 数组中正确传递

    • 验证密钥中没有多余的空格或字符

  3. 模型误差：

    • 确认您使用的是受支持的型号（o3-mini 或 gpt-4o-mini）

    • 检查您的查询不为空

    • 确保你没有超出令牌限制

发展

# Install development dependencies pip install -e ".[dev]" # Run tests pytest -v test_openai.py -s

与原版的差异

  • 增加了对 o3-mini 和 gpt-4o-mini 型号的支持

  • 改进的消息格式

  • 删除温度参数以提高兼容性

  • 更新了文档，其中包含详细的使用示例

  • 增加了模型比较和响应示例

  • 增强安装说明

  • 添加了故障排除指南

执照

MIT 许可证

One-click Deploy
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

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