Langflow Document Q&A Server

Instructions

Implementation Reference

• src/index.ts:53-68 (registration)

  Registration of the 'query_docs' tool including its name, description, and input schema in the ListToolsRequestSchema handler.

      {
        name: 'query_docs',
        description: 'Query the document Q&A system with a prompt',
        inputSchema: {
          type: 'object',
          properties: {
            query: {
              type: 'string',
              description: 'The query prompt to search for in the documents',
            },
          },
          required: ['query'],
        },
      },
    ],
  }));

• src/index.ts:56-66 (schema)

  Input schema definition for the 'query_docs' tool.

    inputSchema: {
      type: 'object',
      properties: {
        query: {
          type: 'string',
          description: 'The query prompt to search for in the documents',
        },
      },
      required: ['query'],
    },
  },

• src/index.ts:70-125 (handler)

  Handler for CallToolRequestSchema that implements the 'query_docs' tool by checking the tool name and making an API call to the document Q&A endpoint with the query, returning the response text.

  this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
    if (request.params.name !== 'query_docs') {
      throw new McpError(
        ErrorCode.MethodNotFound,
        `Unknown tool: ${request.params.name}`
      );
    }
  
    const { query } = request.params.arguments as { query: string };
  
    try {
      const response = await axios.post<QueryResponse>(
        this.apiEndpoint,
        {
          input_value: query,
          output_type: 'chat',
          input_type: 'chat',
          tweaks: {
            'ChatInput-Jrzyb': {},
            'ChatOutput-rzoZb': {},
            'ParseData-hzL7Q': {},
            'File-2Teuj': {},
            'Prompt-ktajI': {},
            'MistralModel-aLZcw': {}
          }
        },
        {
          headers: {
            'Content-Type': 'application/json',
          },
          params: {
            stream: false,
          },
        }
      );
  
      const result = response.data.outputs[0].outputs[0].results.message.text;
  
      return {
        content: [
          {
            type: 'text',
            text: result,
          },
        ],
      };
    } catch (error) {
      if (axios.isAxiosError(error)) {
        throw new McpError(
          ErrorCode.InternalError,
          `API request failed: ${error.message}`
        );
      }
      throw error;
    }
  });