Moss - Real-time Semantic Search for Conversational AI

Integrate Moss into Strands Agents 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.

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 account with project credentials
Python 3.10+
Model provider credentials — Strands Agents defaults to Amazon Bedrock. Configure AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION, or pass a different model provider (see below).

Integration guide

Installation

pip install strands-agents-moss

Environment setup

export MOSS_PROJECT_ID=your_project_id
export MOSS_PROJECT_KEY=your_project_key

Create an agent with Moss search

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())

Choosing a model provider

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

# 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 for all supported providers.

Multi-agent example

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

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=[...])`

Voice & Real-time

AI Frameworks

Developer Tools

Strands Agents

Why use Moss with Strands Agents?

Required tools

Integration guide

Choosing a model provider

Multi-agent example

Configuration

MossSearchTool

Methods

​Why use Moss with Strands Agents?

​Required tools

​Integration guide

​Choosing a model provider

​Multi-agent example

​Configuration

​MossSearchTool

​Methods

Why use Moss with Strands Agents?

Required tools

Integration guide

Choosing a model provider

Multi-agent example

Configuration

MossSearchTool

Methods