mcp_openai_chat
Generate text completions using OpenAI's ChatGPT API, enabling context-aware responses for queries and conversations within the Ontology MCP server.
Instructions
OpenAI ChatGPT API를 사용하여 텍스트 완성을 생성합니다
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| max_tokens | No | 생성할 최대 토큰 수 | |
| messages | Yes | 대화 메시지 배열 | |
| model | Yes | 사용할 모델 (예: gpt-4, gpt-3.5-turbo) | |
| temperature | No | 샘플링 온도(0-2) |
Implementation Reference
- src/tools/index.ts:578-594 (handler)The handler function for the mcp_openai_chat tool, which calls openaiService.chatCompletion and formats the response.
async handler(args: any): Promise<ToolResponse> { try { const result = await openaiService.chatCompletion(args); return { content: [{ type: 'text', text: result }] }; } catch (error) { return { content: [{ type: 'text', text: `OpenAI 채팅 오류: ${error instanceof Error ? error.message : String(error)}` }] }; } - src/tools/index.ts:541-577 (schema)Input schema validating the parameters for the OpenAI chat completion tool.
inputSchema: { type: 'object', properties: { model: { type: 'string', description: '사용할 모델 (예: gpt-4, gpt-3.5-turbo)' }, messages: { type: 'array', items: { type: 'object', properties: { role: { type: 'string', enum: ['system', 'user', 'assistant'] }, content: { type: 'string' } }, required: ['role', 'content'] }, description: '대화 메시지 배열' }, temperature: { type: 'number', description: '샘플링 온도(0-2)', minimum: 0, maximum: 2 }, max_tokens: { type: 'number', description: '생성할 최대 토큰 수' } }, required: ['model', 'messages'] }, - src/index.ts:39-39 (registration)Registration of mcp_openai_chat tool in MCP server capabilities.
mcp_openai_chat: true, - src/services/openai-service.ts:40-90 (helper)The supporting service method that performs the actual OpenAI Chat Completions API request using axios.
async chatCompletion(args: { model: string; messages: Array<{ role: string; content: string }>; temperature?: number; max_tokens?: number; stream?: boolean; }): Promise<string> { try { if (!OPENAI_API_KEY) { throw new McpError( ErrorCode.InternalError, 'OPENAI_API_KEY가 설정되지 않았습니다.' ); } const response = await axios.post( `${OPENAI_API_BASE}/chat/completions`, { model: args.model, messages: args.messages, temperature: args.temperature ?? 0.7, max_tokens: args.max_tokens, stream: args.stream ?? false }, { headers: { 'Content-Type': 'application/json', 'Authorization': `Bearer ${OPENAI_API_KEY}` } } ); return JSON.stringify(response.data, null, 2); } catch (error) { if (axios.isAxiosError(error)) { const statusCode = error.response?.status; const responseData = error.response?.data; throw new McpError( ErrorCode.InternalError, `OpenAI API 오류 (${statusCode}): ${ typeof responseData === 'object' ? JSON.stringify(responseData, null, 2) : responseData || error.message }` ); } throw new McpError(ErrorCode.InternalError, `채팅 완성 요청 실패: ${formatError(error)}`); } }