Skip to main content
Glama
enesjakozh
mzxrai

MCP OpenAI Server

by mzxrai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

MCP OpenAI 서버

Claude에서 바로 OpenAI의 모델을 원활하게 사용할 수 있게 해주는 MCP(Model Context Protocol) 서버입니다.

특징

  • OpenAI의 채팅 모델과 직접 통합

  • 다음을 포함한 다양한 모델 지원:

    • gpt-4o

    • gpt-4o-미니

    • o1-미리보기

    • 오원미니

  • 간단한 메시지 전달 인터페이스

  • 기본 오류 처리

Related MCP server: OpenAI Agents MCP Server

필수 조건

설치

먼저, Claude Desktop 앱이 설치되어 있고 OpenAI API 키를 요청했는지 확인하세요.

claude_desktop_config.json 에 이 항목을 추가하세요(Mac에서는 ~/Library/Application\ Support/Claude/claude_desktop_config.json 에서 찾을 수 있습니다).

지엑스피1

이 구성을 사용하면 Claude Desktop이 필요할 때마다 OpenAI MCP 서버를 실행할 수 있습니다.

용법

Claude와 대화를 시작하세요. OpenAI의 모델을 사용하고 싶으면 Claude에게 사용해 달라고 요청하세요.

예를 들어, 이렇게 말할 수 있습니다.

Can you ask o1 what it thinks about this problem?

또는,

What does gpt-4o think about this?

현재 서버는 다음 모델을 지원합니다.

  • gpt-4o(기본값)

  • gpt-4o-미니

  • o1-미리보기

  • 오원미니

도구

  1. openai_chat

    • OpenAI의 채팅 완료 API에 메시지를 보냅니다.

    • 인수:

      • messages : 메시지 배열(필수)

      • model : 사용할 모델(선택 사항, 기본값은 gpt-4o)

문제들

알파 소프트웨어이므로 버그가 있을 수 있습니다. 문제가 발생하면 Claude Desktop의 MCP 로그를 확인하세요.

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

개발

# Install dependencies
pnpm install

# Build the project
pnpm build

# Watch for changes
pnpm watch

# Run in development mode
pnpm dev

요구 사항

  • 노드.js >= 18

  • OpenAI API 키

검증된 플랫폼

  • [x] 맥OS

  • [ ] 리눅스

특허

MIT

작가

mzxrai

Available Tools

1 tool
openai_chatB

Use this tool when a user specifically requests to use one of OpenAI's models (gpt-4o, gpt-4o-mini, o1-preview, o1-mini). This tool sends messages to OpenAI's chat completion API using the specified model.

ParametersJSON Schema
NameRequiredDescriptionDefault
messagesYesArray of messages to send to the API
modelNoModel to use for completion (gpt-4o, gpt-4o-mini, o1-preview, o1-mini)gpt-4o

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the action ('sends messages') but omits critical behavioral details like authentication requirements, rate limits, error handling, or response format. For a tool interacting with an external API, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences that directly address purpose and usage. It's front-loaded with the usage condition, though it could be slightly more structured. There's minimal waste, earning a high score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of an API call tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication, error cases, response structure, and operational constraints, which are crucial for effective tool use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents the parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples or usage tips). This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'sends messages to OpenAI's chat completion API using the specified model.' It specifies the verb ('sends'), resource ('messages'), and target ('OpenAI's chat completion API'), though it doesn't need to distinguish from siblings since none exist. The mention of specific models adds precision.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides some usage guidance: 'Use this tool when a user specifically requests to use one of OpenAI's models.' This implies context but lacks explicit when-not-to-use scenarios or alternatives. With no sibling tools, the guidance is adequate but not comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedopenai_chat
Deploy Server
Context Every Agent Can ShareAgents share what they learn, hand off work, and keep it when you switch models. Start with 5 GB free.fulcradynamics.comAd

TDQS

B3.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

The single tool name 'openai_chat' follows a consistent pattern (noun_verb-like structure), and with only one tool, there is no inconsistency to evaluate.

Tool Count2/5

A single tool is too few for a server named 'MCP OpenAI Server', which suggests broader OpenAI functionality. The scope feels thin, as it only covers chat completions, lacking other common operations like embeddings or fine-tuning.

Completeness2/5

The tool surface is severely incomplete for an OpenAI server. It only provides chat completions, missing essential operations such as embeddings, image generation, file handling, or model management, which are core to OpenAI's API.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • openai-tool2mcp

    alohays
    A
    license
    B
    quality
    F
    maintenance
    A lightweight bridge that wraps OpenAI's built-in tools (like web search and code interpreter) as Model Context Protocol servers, enabling their use with Claude and other MCP-compatible models.
    4
    12
    MIT

  • OpenAI Agents MCP Server

    lroolle
    F
    license
    B
    quality
    D
    maintenance
    A Model Context Protocol server that enables Claude users to access specialized OpenAI agents (web search, file search, computer actions) and a multi-agent orchestrator through the MCP protocol.
    4
    10
    -

  • SwiftOpenAI MCP Server

    jamesrochabrun
    A
    license
    Not graded
    quality
    C
    maintenance
    A universal server that enables MCP-compatible clients (like Claude Desktop, Cursor, VS Code) to access OpenAI's APIs for chat completions, image generation, embeddings, and model listing through a standardized interface.
    13 npm
    7
    MIT

Appeared in Searches