Ontology MCP

Instructions

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)}`);
    }
  }