Provides comprehensive documentation and guidance for AWS AgentCore, enabling users to build, secure, monitor, and manage AI agents at scale with enterprise-grade features including identity management, API gateway integration, observability, code interpretation, and memory storage.
This MCP server provides comprehensive documentation about AWS AgentCore to your GenAI tools, enabling you to build production-ready AI agents with enterprise-grade security, observability, and scalability.
What is AWS AgentCore?
AWS AgentCore is a comprehensive framework for building, securing, monitoring, and managing AI agents at scale on Amazon Bedrock. It provides:
- AgentCore Identity: Centralized management of agent identities and credentials
- AgentCore Gateway: Universal integration layer for APIs and external services
- AgentCore Observability: Advanced tracing, monitoring, and debugging capabilities
- AgentCore Code Interpreter: Secure code execution within sandboxed sessions
- AgentCore Memory: Short-term and long-term memory storage for context-aware agents
Prerequisites
The usage methods below require uv to be installed on your system. You can install it by following the official installation instructions.
Installation
You can use the AWS AgentCore MCP server with 40+ applications that support MCP servers, including Amazon Q Developer CLI, Anthropic Claude Code, Cline, and Cursor.
Q Developer CLI example
See the Q Developer CLI documentation for instructions on managing MCP configuration.
In ~/.aws/amazonq/mcp.json
:
Claude Code example
See the Claude Code documentation for instructions on managing MCP servers.
Cline example
See the Cline documentation for instructions on managing MCP configuration.
Provide Cline with the following information:
Cursor example
See the Cursor documentation for instructions on managing MCP configuration.
In ~/.cursor/mcp.json
:
Available Tools
The MCP server provides the following documentation tools:
quickstart()
- Get started with AWS AgentCore SDKagentcore_identity()
- Learn about secure agent authentication and authorizationagentcore_gateway()
- Integrate external APIs and servicesagentcore_observability()
- Monitor and debug agents in productionagentcore_code_interpreter()
- Execute code securely in agentsagentcore_memory()
- Build context-aware agents with persistent memoryagentcore_tools()
- Integrate tools and extend agent capabilities
Quick Testing
You can quickly test the MCP server using the MCP Inspector:
Note: This requires npx to be installed on your system. It comes bundled with Node.js.
The Inspector is also useful for troubleshooting MCP server issues as it provides detailed connection and protocol information. For an in-depth guide, have a look at the MCP Inspector documentation.
Server Development
Example Usage
Once installed, you can ask your AI assistant questions like:
- "How do I get started with AWS AgentCore?"
- "Show me how to set up AgentCore Identity for secure authentication"
- "How do I integrate external APIs using AgentCore Gateway?"
- "What observability features does AgentCore provide?"
- "How can I add code execution capabilities to my agent?"
- "How do I implement memory in my AgentCore agent?"
- "What tools can I integrate with my AgentCore agent?"
The MCP server will provide comprehensive documentation and code examples for each AgentCore component.
Contributing ❤️
We welcome contributions! See our Contributing Guide for details on:
- Reporting bugs & features
- Development setup
- Contributing via Pull Requests
- Code of Conduct
- Reporting of security issues
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
Security
See CONTRIBUTING for more information.
Tools
Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.
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