AWS Bedrock AgentCore

This guide walks you through deploying the AWS Bedrock AgentCore MCP Server on TrueFoundry and registering it with the TrueFoundry MCP Gateway. Once registered, your agents and AI coding assistants can search and fetch AWS Bedrock AgentCore documentation through a centralized, managed endpoint.

What is AWS Bedrock AgentCore MCP?

The AWS Bedrock AgentCore MCP server provides AI tools with direct access to Amazon Bedrock AgentCore documentation. It enables LLMs and coding assistants to search, retrieve, and understand AgentCore concepts — covering runtime deployment, gateway connectivity, memory management, and agent lifecycle workflows.

The AWS Bedrock AgentCore MCP server is a documentation-only tool. It does not provision AWS resources, deploy agents, or make API calls to AWS services on your behalf. Its sole purpose is to give AI assistants access to the AgentCore documentation so they can help you write code, understand concepts, and troubleshoot issues related to Amazon Bedrock AgentCore services such as Runtime, Memory, Code Interpreter, Browser, Gateway, Observability, and Identity.

Available Tools

The MCP server exposes the following tools:

Tool	Description
search_agentcore_docs	Search curated AgentCore documentation and return ranked results with contextual snippets
fetch_agentcore_doc	Fetch full document content by URL for in-depth understanding of specific pages
manage_agentcore_runtime	Get step-by-step documentation on deploying and managing agents in AgentCore Runtime, including CLI workflows, code patterns, and troubleshooting
manage_agentcore_memory	Get documentation on creating and managing AgentCore Memory resources, covering short-term memory, long-term memory, and semantic memory strategies
manage_agentcore_gateway	Get documentation on deploying and managing MCP Gateways in AgentCore, including target management, authentication setup, and CLI commands

Prerequisites

Before you begin, ensure you have:

TrueFoundry Account: A TrueFoundry account with a configured workspace
MCP Gateway Access: Follow the MCP Gateway Getting Started guide to set up your MCP Server Group

Step 1: Create the MCP Server

The server wraps the official AWS Bedrock AgentCore MCP package and exposes it over HTTP using FastMCP.

#!/usr/bin/env python3
"""
AWS Bedrock AgentCore MCP Server HTTP Wrapper

Runs the AWS Bedrock AgentCore MCP server with HTTP transport.
"""

import os
import sys

# Ensure cache is ready before importing the server
from awslabs.amazon_bedrock_agentcore_mcp_server.utils import cache
cache.ensure_ready()

# Import the MCP server
from awslabs.amazon_bedrock_agentcore_mcp_server.server import mcp


def main():
    """Run the AWS Bedrock AgentCore MCP server with HTTP transport."""
    port = int(os.environ.get("PORT", "3000"))
    host = os.environ.get("HOST", "0.0.0.0")

    # Configure server settings
    mcp.settings.host = host
    mcp.settings.port = port

    # Disable DNS rebinding protection for production deployment
    # This allows requests from any host (e.g., gateway.truefoundry.ai)
    mcp.settings.transport_security.enable_dns_rebinding_protection = False

    print("=" * 60)
    print("AWS Bedrock AgentCore MCP Server")
    print("=" * 60)
    print(f"Host: {host}")
    print(f"Port: {port}")
    print(f"MCP endpoint: http://{host}:{port}/mcp")
    print("=" * 60)
    sys.stdout.flush()

    # Run the MCP server with streamable HTTP transport
    mcp.run(transport="streamable-http")


if __name__ == "__main__":
    main()

# AWS Bedrock AgentCore MCP Server Dependencies
fastmcp>=2.0.0
awslabs-amazon-bedrock-agentcore-mcp-server

# AWS Bedrock AgentCore MCP Server
# Deployable as a service on TrueFoundry with /mcp endpoint

FROM python:3.11-slim

# Set working directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Copy requirements and install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy application files
COPY main.py .

# Environment variables
ENV PORT=3000
ENV HOST=0.0.0.0
ENV FASTMCP_LOG_LEVEL=INFO

# Expose port
EXPOSE 3000

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=10s --retries=3 \
    CMD curl -f http://localhost:3000/mcp || exit 1

# Start the MCP server
CMD ["python", "main.py"]

You can find the complete example code at: AWS AgentCore MCP Server Repository

Step 2: Run Locally

# Install dependencies
pip install -r requirements.txt

# Run the server
python main.py

Your MCP server will be available at http://localhost:3000/mcp.

Step 3: Deploy on TrueFoundry

Deploy this MCP server as a service on TrueFoundry:

Create a new Service in your TrueFoundry workspace.
Point to the GitHub repository or use the Dockerfile above.
Optionally set environment variables for AWS access:

Variable	Description	Default
`PORT`	Port to run the server on	`3000`
`HOST`	Host to bind to	`0.0.0.0`
`FASTMCP_LOG_LEVEL`	Log level (DEBUG, INFO, WARNING, ERROR)	`INFO`
`AWS_ACCESS_KEY_ID`	AWS Access Key ID	-
`AWS_SECRET_ACCESS_KEY`	AWS Secret Access Key	-
`AWS_REGION`	AWS Region	-

Deploy the service. Once running, your deployment will look like this:

TrueFoundry deployment dashboard showing the AWS AgentCore MCP server running with active pods

Step 4: Register in TrueFoundry MCP Gateway

Once the service is deployed, register it with the TrueFoundry MCP Gateway:

Navigate to MCP Server Groups in the TrueFoundry dashboard.
Select your MCP Server Group (or create one following the Getting Started guide).
Click Add MCP Server and fill in the following details:

Field	Value
Name	`aws-agentcore-mcp`
Description	AWS Bedrock AgentCore MCP server for searching and fetching AgentCore documentation
URL	`https://<your-service-endpoint>/mcp`
Transport	Streamable HTTP
Authentication	No Auth

TrueFoundry MCP server registration form showing name, description, URL, and transport configuration for the AWS AgentCore MCP server

Save the configuration. The MCP Gateway will connect to your server and discover the available tools.

Step 5: Verify the Integration

After registration, navigate to your MCP server in the dashboard. You should see all 5 tools discovered and available:

TrueFoundry MCP Gateway showing the AWS AgentCore MCP server with 5 connected tools including search_agentcore_docs, fetch_agentcore_doc, manage_agentcore_runtime, manage_agentcore_memory, and manage_agentcore_gateway

You can click Try on any tool to test it directly from the dashboard.

Next Steps

Use in an agent: Connect this MCP server to an AI agent using the Implementation Recipes
Add authentication: Secure your MCP server with authentication and access control
Create a Virtual MCP Server: Combine this with other MCP servers into a Virtual MCP Server for unified tool access

Get Started

LLM Gateway

MCP Registry and Gateway

Skills Registry

Prompt Registry

Guardrails and Security

Observability

Deployment

Admin Guide

Chat

Messages

Embeddings

Rerank

Responses

Image

Audio

Batch

Files

Fine-tuning

Moderations

Models

What is AWS Bedrock AgentCore MCP?

Available Tools

Prerequisites

Step 1: Create the MCP Server

Step 2: Run Locally

Step 3: Deploy on TrueFoundry

Step 4: Register in TrueFoundry MCP Gateway

Step 5: Verify the Integration

Next Steps

​What is AWS Bedrock AgentCore MCP?

​Available Tools

​Prerequisites

​Step 1: Create the MCP Server

​Step 2: Run Locally

​Step 3: Deploy on TrueFoundry

​Step 4: Register in TrueFoundry MCP Gateway

​Step 5: Verify the Integration

​Next Steps

What is AWS Bedrock AgentCore MCP?

Available Tools

Prerequisites

Step 1: Create the MCP Server

Step 2: Run Locally

Step 3: Deploy on TrueFoundry

Step 4: Register in TrueFoundry MCP Gateway

Step 5: Verify the Integration

Next Steps