> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cognee.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Strands
> Add persistent memory to Strands agents with Cognee.
Give your [Strands](https://strandsagents.com/) agents persistent memory powered by cognee. Built on cognee v1.0, the integration exposes two tools — `remember` and `recall` — that write to a permanent knowledge graph or a lightweight session cache, and survive across agent instances.
## Why Use This Integration
* **Two memory tiers**: Write straight to the permanent knowledge graph, or to a cheap per-session cache that you promote later
* **Natural language recall**: Retrieve stored knowledge with graph traversal and vector similarity
* **Cross-session memory**: Context persists across agent instances and restarts
* **Drop-in tools**: `cognee_tools()` returns ready-to-use Strands tools
## Installation
```bash theme={null}
pip install cognee-integration-strands
```
Requires Python 3.10+. Pins `cognee>=1.0.0,<=1.1.2` and `strands-agents>=1.42.0,<2.0.0`.
## Quick Start
Set your LLM key (cognee extracts knowledge with an LLM), then attach the tools:
```bash theme={null}
export LLM_API_KEY="your-openai-api-key-here" # used by cognee
```
```python theme={null}
import os
import cognee
from cognee_integration_strands import cognee_tools, run_cognee_task
from strands import Agent
from strands.models.openai import OpenAIModel
run_cognee_task(cognee.forget(everything=True)) # optional: start fresh
model = OpenAIModel(client_args={"api_key": os.getenv("LLM_API_KEY")}, model_id="gpt-4o")
agent = Agent(model=model, tools=cognee_tools())
# Store information
agent("Remember that we signed a contract with Meditech Solutions for £1.2M.")
# Retrieve it (even from a fresh agent — memory is persistent)
print(agent("What is the value of the Meditech Solutions contract?"))
```
## Tools
`cognee_tools(session_id=None, *, remember_kwargs=None, recall_kwargs=None)` returns a list of two tools:
| Tool | Description |
| ---------- | ------------------------------------------------------------------------------------ |
| `remember` | Store information in memory for later retrieval (wraps `cognee.remember`) |
| `recall` | Search and retrieve stored information with natural language (wraps `cognee.recall`) |
## Session Memory
By default, `remember` writes straight to the **permanent knowledge graph**. Pass a `session_id` to write to that session's lightweight cache instead, then promote the cache into the graph when you're ready:
```python theme={null}
SESSION_ID = "mission-briefing"
session_agent = Agent(
model=model,
tools=cognee_tools(session_id=SESSION_ID, remember_kwargs={"self_improvement": False}),
)
# ... use session_agent throughout the session ...
# Promote the session cache into the permanent graph
run_cognee_task(cognee.improve(session_ids=[SESSION_ID]))
```
Passing `remember_kwargs={"self_improvement": False}` keeps session writes in cache-only mode until you call `cognee.improve(...)`. Without a `session_id`, writes go directly to the permanent graph.
## How It Works
1. **Remember**: Stores data in cognee's memory — the permanent graph, or a session cache when `session_id` is set
2. **Recall**: Retrieves relevant information via cognee's recall pipeline
3. **Auto-Processing**: cognee extracts entities, relationships, and context automatically
4. **Background loop**: cognee's async API runs on a dedicated background event loop; `run_cognee_task()` handles this transparently
***
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