> ## Documentation Index
> Fetch the complete documentation index at: https://docs.moss.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Strands Agents

> Give Strands Agents sub-10ms semantic retrieval from a Moss knowledge base.

Integrate Moss into [Strands Agents](https://strandsagents.com) as a search tool. The agent calls `moss_search` automatically when it needs to look something up — no retrieval glue code required.

> **Note:** For a complete example, see the [Strands Agents cookbook](https://github.com/usemoss/moss/tree/main/packages/strands-agents-moss/examples).

## Why use Moss with Strands Agents?

Strands Agents exposes tools as first-class primitives. `MossSearchTool` wraps a Moss index as a Strands-compatible tool, so the agent decides when to retrieve — and gets answers back in under 10 ms.

## Required tools

* [Moss](https://www.moss.dev/) account with project credentials
* Python 3.10+
* **Model provider credentials** — Strands Agents defaults to [Amazon Bedrock](https://aws.amazon.com/bedrock/). Configure `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, and `AWS_REGION`, or pass a different model provider (see below).

## Integration guide

<Steps>
  <Step title="Installation">
    ```bash theme={null}
    pip install strands-agents-moss
    ```
  </Step>

  <Step title="Environment setup">
    ```bash theme={null}
    export MOSS_PROJECT_ID=your_project_id
    export MOSS_PROJECT_KEY=your_project_key
    ```
  </Step>

  <Step title="Create an agent with Moss search">
    ```python theme={null}
    import asyncio
    import os
    from strands import Agent
    from strands_agents_moss import MossSearchTool

    async def main():
        moss = MossSearchTool(
            project_id=os.getenv("MOSS_PROJECT_ID"),
            project_key=os.getenv("MOSS_PROJECT_KEY"),
            index_name="my-index",
        )
        await moss.load_index()

        agent = Agent(tools=[moss.tool])
        agent("What is your refund policy?")

    asyncio.run(main())
    ```
  </Step>
</Steps>

## Choosing a model provider

Strands defaults to Amazon Bedrock. To use a different provider, pass a `model` argument:

```python theme={null}
# Assumes you already created moss = MossSearchTool(...) and awaited moss.load_index()

# OpenAI
from strands.models.openai import OpenAIModel
agent = Agent(model=OpenAIModel("gpt-4o"), tools=[moss.tool])

# Anthropic
from strands.models.anthropic import AnthropicModel
agent = Agent(model=AnthropicModel("claude-sonnet-4-20250514"), tools=[moss.tool])
```

See the [Strands model providers docs](https://strandsagents.com/docs/user-guide/concepts/model-providers/) for all supported providers.

## Multi-agent example

Moss tools compose with Strands' agents-as-tools pattern:

```python theme={null}
import asyncio
from strands import Agent
from strands_agents_moss import MossSearchTool

async def main():
    moss = MossSearchTool(index_name="product-docs")
    await moss.load_index()

    researcher = Agent(
        system_prompt="You are a research assistant. Use moss_search to find information.",
        tools=[moss.tool],
    )

    orchestrator = Agent(
        system_prompt="You coordinate research tasks. Delegate questions to the researcher.",
        tools=[researcher.as_tool(
            name="researcher",
            description="A research assistant with access to the knowledge base",
        )],
    )

    orchestrator("Summarise our return and refund policies.")

asyncio.run(main())
```

## Configuration

### MossSearchTool

| Parameter          | Default                                | Description                                        |
| ------------------ | -------------------------------------- | -------------------------------------------------- |
| `project_id`       | `MOSS_PROJECT_ID` env var              | Moss project ID                                    |
| `project_key`      | `MOSS_PROJECT_KEY` env var             | Moss project key                                   |
| `index_name`       | (required)                             | Name of the Moss index to query                    |
| `tool_name`        | `moss_search`                          | Tool name exposed to the LLM                       |
| `tool_description` | *(auto-generated)*                     | Tool description exposed to the LLM                |
| `top_k`            | `5`                                    | Number of results to retrieve per query            |
| `alpha`            | `0.8`                                  | Blend: `1.0` = semantic only, `0.0` = keyword only |
| `result_prefix`    | `Relevant knowledge base results:\n\n` | Prefix prepended to formatted results              |

### Methods

| Method          | Description                                                                   |
| --------------- | ----------------------------------------------------------------------------- |
| `load_index()`  | Async. Pre-load the Moss index — call once at startup                         |
| `search(query)` | Async. Query Moss and return formatted results as a string                    |
| `tool`          | Property. Returns the Strands-compatible tool to pass to `Agent(tools=[...])` |