basic-memory

Instructions

Implementation Reference

• src/basic_memory/mcp/tools/chatgpt_tools.py:141-191 (handler)

  The handler function for the MCP tool named 'fetch'. It retrieves the full content of a document by its ID using the underlying 'read_note' tool, formats it into a JSON structure compatible with ChatGPT/OpenAI expectations, and returns it wrapped in the MCP content array format.

  @mcp.tool(description="Fetch the full contents of a search result document")
  async def fetch(
      id: str,
      context: Context | None = None,
  ) -> List[Dict[str, Any]]:
      """ChatGPT/OpenAI MCP fetch adapter returning a single text content item.
  
      Args:
          id: Document identifier (permalink, title, or memory URL)
          context: Optional FastMCP context passed through for auth/session data
  
      Returns:
          List with one dict: `{ "type": "text", "text": "{...JSON...}" }`
          where the JSON body includes `id`, `title`, `text`, `url`, and metadata.
      """
      track_mcp_tool("fetch")
      logger.info(f"ChatGPT fetch request: id='{id}'")
  
      try:
          # ChatGPT tools don't expose project parameter, so use default project
          config = ConfigManager().config
          default_project = config.default_project
  
          # Call underlying read_note function
          content = await read_note.fn(
              identifier=id,
              project=default_project,  # Use default project for ChatGPT
              page=1,
              page_size=10,  # Default pagination
              context=context,
          )
  
          # Format the document for ChatGPT
          document = _format_document_for_chatgpt(content, id)
  
          logger.info(f"Fetch completed: id='{id}', content_length={len(document.get('text', ''))}")
  
          # Return in MCP content array format as required by OpenAI
          return [{"type": "text", "text": json.dumps(document, ensure_ascii=False)}]
  
      except Exception as e:
          logger.error(f"ChatGPT fetch failed for id '{id}': {e}")
          error_document = {
              "id": id,
              "title": "Fetch Error",
              "text": f"Failed to fetch document: {str(e)[:200]}",
              "url": id,
              "metadata": {"error": "Fetch failed"},
          }
          return [{"type": "text", "text": json.dumps(error_document, ensure_ascii=False)}]