> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://help.getzep.com/v2/sdk-reference/deprecated/document/gets-a-document-from-a-document-collection-by-uuid/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://help.getzep.com/_mcp/server. # Gets a Document from a DocumentCollection by UUID GET https://api.getzep.com/api/v2/collections/{collectionName}/documents/uuid/{documentUUID} Returns specified Document from a DocumentCollection. Reference: https://help.getzep.com/v2/sdk-reference/deprecated/document/gets-a-document-from-a-document-collection-by-uuid ## Request ### Path parameters - `collectionName` (string, required) — Name of the Document Collection - `documentUUID` (string, required) — UUID of the Document to be updated ## Response ### 200 OK - `content` (string, optional) - `created_at` (string, optional) - `document_id` (string, optional) - `embedding` (list of double, optional) - `is_embedded` (boolean, optional) - `metadata` (map from string to any, optional) - `updated_at` (string, optional) - `uuid` (string, optional) ## Errors ### 400 Bad Request Error Bad Request - `message` (string, optional) ### 401 Unauthorized Error Unauthorized - `message` (string, optional) ### 500 Internal Server Error Internal Server Error - `message` (string, optional) ## Examples **Request** ```json {} ``` **Response** ```json { "content": "This document contains the quarterly financial report for Q1 2024, including revenue, expenses, and profit analysis.", "created_at": "2024-04-15T09:30:00Z", "document_id": "doc-789456123", "embedding": [ 0.12345, -0.98765, 0.45678, 0.23456, -0.34567, 0.56789, -0.12345, 0.6789, -0.23456, 0.34567 ], "is_embedded": true, "metadata": { "author": "Jane Doe", "department": "Finance", "confidential": false, "tags": [ "financial", "Q1", "report" ] }, "updated_at": "2024-04-20T16:45:00Z", "uuid": "3fa85f64-5717-4562-b3fc-2c963f66afa6" } ``` > Zep unifies business data, documents, and conversations into shared, governed context that agents can retrieve for their tasks.