Omi Memories MCP Server

Implementation Reference

• src/server.ts:46-86 (handler)

  The handler function that executes the 'fetch-memories' tool logic. It makes an API request to fetch conversations for a specific user ID, formats the data into a readable text summary including IDs, times, titles, overviews, categories, emojis, and transcripts, and returns it as MCP content. Includes error handling for Axios errors.

      try {
        const response = await axios.get(`${EXPRESS_API_URL}/memories`, {
          params: { uid: SPECIFIC_USER_ID }
        });
  
        const conversations: Conversation[] = response.data.conversations;
  
        // Format conversations for better readability
        const formattedText = conversations.map(conv => {
          return `
  Memory: ${conv.id}
  Time: ${new Date(conv.created_at).toLocaleString()}
  Title: ${conv.structured.title}
  Overview: ${conv.structured.overview}
  Category: ${conv.structured.category}
  Emoji: ${conv.structured.emoji}
  Transcript:
  ${conv.transcript_segments.map(segment => `  ${segment.speaker}: ${segment.text}`).join('\n')}
  -------------------
          `.trim();
        }).join('\n\n');
  
        return {
          content: [{
            type: "text",
            text: formattedText
          }]
        };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          return {
            content: [{
              type: "text",
              text: `Error: Failed to fetch memories: ${error.message}`
            }],
            isError: true
          };
        }
        throw error;
      }
    }

• src/server.ts:43-87 (registration)

  Registration of the 'fetch-memories' tool using McpServer.tool() method, specifying the tool name, an empty input schema (no parameters), and an inline async handler function.

    "fetch-memories",
    {},  // No parameters needed since we're using a specific user ID
    async () => {
      try {
        const response = await axios.get(`${EXPRESS_API_URL}/memories`, {
          params: { uid: SPECIFIC_USER_ID }
        });
  
        const conversations: Conversation[] = response.data.conversations;
  
        // Format conversations for better readability
        const formattedText = conversations.map(conv => {
          return `
  Memory: ${conv.id}
  Time: ${new Date(conv.created_at).toLocaleString()}
  Title: ${conv.structured.title}
  Overview: ${conv.structured.overview}
  Category: ${conv.structured.category}
  Emoji: ${conv.structured.emoji}
  Transcript:
  ${conv.transcript_segments.map(segment => `  ${segment.speaker}: ${segment.text}`).join('\n')}
  -------------------
          `.trim();
        }).join('\n\n');
  
        return {
          content: [{
            type: "text",
            text: formattedText
          }]
        };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          return {
            content: [{
              type: "text",
              text: `Error: Failed to fetch memories: ${error.message}`
            }],
            isError: true
          };
        }
        throw error;
      }
    }
  );

• src/server.ts:44-44 (schema)

  Empty Zod schema object indicating the tool takes no input parameters.

  {},  // No parameters needed since we're using a specific user ID

• src/server.ts:16-39 (helper)

  TypeScript interface defining the Conversation type used to type the API response data in the handler, including structured metadata and transcript segments.

  interface Conversation {
    id: string;
    created_at: string;
    started_at: string;
    finished_at: string;
    source: string;
    structured: {
      emoji: string;
      events: any[];
      overview: string;
      title: string;
      action_items: any[];
      category: string;
    };
    transcript_segments: {
      is_user: boolean;
      start: number;
      end: number;
      text: string;
      speaker_id: number;
      speaker: string;
      person_id: null;
    }[];
  }