remember
Store text or file content in memory. Omit session_id to persist a searchable knowledge graph; include it to keep data in a quick session cache.
Instructions
Store data in memory.
Two modes depending on whether session_id is provided:
Without session_id (permanent memory): Runs the full add + cognify pipeline to ingest data and build the knowledge graph.
With session_id (session memory): Stores the data in the session cache only. Fast, no entity extraction. Omit session_id when the content should be stored as permanent graph memory.
Pass either data (text) or filename + content_base64 (a file
upload, up to 10 MB), not both. File uploads are permanent-memory
only and don't support session_id.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | The text content to store. Mutually exclusive with filename/content_base64. | |
| filename | No | Original filename for a file upload. Used to derive the stored document's name. Requires content_base64. | |
| background | No | Queue permanent ingestion as a background task and return immediately instead of waiting for the pipeline. Use when the caller has a request deadline shorter than ingestion takes. Ignored with session_id, which is already fast. Errors surface via cognify_status, not the return value. | |
| session_id | No | Session ID. When set, stores in session cache only. | |
| dataset_name | No | Target dataset name. Defaults to the current MCP client's agent-scoped dataset (e.g. "cursor_vscode_memory"), or "main_dataset" if no client identity is detected. | |
| custom_prompt | No | Custom prompt for entity extraction (permanent mode only). | |
| content_base64 | No | Base64-encoded file content to ingest. Requires filename. |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |