> For the complete documentation index, see [llms.txt](https://notara.gitbook.io/notara-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://notara.gitbook.io/notara-docs/connectors/memory.md).

# Memory

The agent's persistent memory system — saves and recalls facts, decisions, and preferences across conversations.

## What It Enables

| Tool              | Capability    | Description                                                                |
| ----------------- | ------------- | -------------------------------------------------------------------------- |
| `save_memory`     | `write`       | Save a piece of information under a key and category                       |
| `recall_memory`   | `read`        | Retrieve memories by key, category, or get a summary of all stored entries |
| `search_memories` | `read`        | Search memories by keyword or semantic similarity                          |
| `delete_memory`   | `destructive` | Delete a specific memory entry                                             |
| `memory_stats`    | `read`        | Get counts of stored memories by category                                  |

Memories are categorized as `decision`, `insight`, `action`, `user_preference`, or `general`. Semantic search uses pgvector embeddings when available; falls back to keyword search.

## Setup

**No API key required.** Memory is an internal Notara service — it stores data directly in your workspace's database, scoped to your tenant.

The connector is always available and requires no configuration. You can view and manage stored memories from the **Memory** page in the Notara dashboard.

## Example Prompts

> "Remember that we decided to use Stripe for billing, not Paddle."

> "What do you know about our Q3 marketing strategy?"

> "Search your memory for anything related to the API rate limit decision."

> "Forget everything saved under the 'old\_pricing' key."


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://notara.gitbook.io/notara-docs/connectors/memory.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.