MCP for executing strands agents
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# Strands Agent MCP A Model Context Protocol (MCP) server for executing Strands agents. This project provides a simple way to integrate Strands agents with Amazon Q and other MCP-compatible systems. > **IMPORTANT**: This project is currently in alpha stage and not yet published on PyPI. ## Overview Strands Agent MCP is a bridge between the Strands agent framework and the Model Context Protocol (MCP). It allows you to: - Register Strands agents as MCP tools - Execute Strands agents through MCP - Find agents by specific skills The project uses a plugin architecture that makes it easy to add new agents without modifying the core code. ## Installation > Note: This package is not yet available on PyPI. You'll need to install it from source. ```bash # Clone the repository git clone https://github.com/yourusername/strands-agent-mcp.git cd strands-agent-mcp # Install the package pip install -e . ``` ## Usage ### Starting the MCP Server ```bash strands-agent-mcp ``` This will start the MCP server. ### Environment Variables The server supports the following environment variables: - `PLUGIN_PATH`: Custom path to look for plugins (default: ".") - `PLUGIN_NAMESPACE`: Custom namespace prefix for plugins (default: 'sap_mcp_plugin') ### Creating Agent Plugins To create a new agent plugin, create a Python package with a name that starts with `sap_mcp_plugin_` (sap stands for strands agent plugin). Your package should implement a `build_agents` function that returns a list of `AgentEntry` objects: ```python from typing import List from boto3 import Session from strands import Agent from strands.models import BedrockModel from strands_agent_mcp.registry import AgentEntry def build_agents() -> List[AgentEntry]: return [ AgentEntry( name="my-agent", agent=Agent( model=BedrockModel(boto_session=Session(region_name="us-west-2")) ), skills=["general-knowledge", "coding"] ) ] ``` …
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