Development

AWS Bedrock KB Retrieval

BYawslabs★ 7,894GRADE B

Query Amazon Bedrock Knowledge Bases using natural language to retrieve relevant information from your data sources.

⚡Config Installation

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "aws-bedrock-kb-retrieval": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-aws-bedrock-kb-retrieval"
      ]
    }
  }
}

* Note: Requires restart of Claude Desktop app.

View Source Code→

Deployment Infrastructure

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Adoption Framework for AWS Bedrock KB Retrieval

Before installing any skill, define a clear objective and measurable outcome. A useful implementation question is: what workflow becomes faster, safer, or more reliable after this skill is active? If that answer is vague, delay rollout and tighten scope first.

For most teams, a low-risk pattern is preview-first rollout with one owner, one test scenario, and one rollback plan. Capture failures in a structured log so quality decisions are evidence-based. This is especially important for skills that touch file systems, external APIs, or automation chains with downstream side effects.

Define success metrics before installation.
Validate permission scope against policy boundaries.
Run one controlled pilot and document failure categories.
Promote only after acceptance checks pass consistently.

Pre-Deployment Review Questions

Use these questions before enabling the skill in shared environments. They reduce surprise incidents and make approval decisions consistent across teams.

What data can this skill read, write, or transmit by default?
Which failures are recoverable automatically and which require manual stop?
Do we have verifiable logs that prove safe behavior under load?
Is rollback tested, documented, and assigned to a clear owner?

If any answer is unclear, keep rollout in preview and close the gap before production use.

Editorial Review Snapshot

This listing includes an editorial QA layer in addition to automated rendering. Review status is based on documentation depth, content uniqueness, and operational safety signals from the upstream repository.

Last scan date: 2026-03-14
README depth: 1028 words
Content diversity score: 0.55 (higher is better)
Template signal count: 0
Index status: Index eligible

Recommendation: Pilot in a bounded environment first. Confirm observability and ownership before promoting to shared workflows.

Skill Implementation Board

Actionable utility module for rollout decisions. Use the inputs below to choose a deployment path, then execute the checklist and record an output note.

Input: Security Grade

Input: Findings

Input: README Depth

1028 words

Input: Index State

Eligible

Decision Trigger	Action	Expected Output
Input: risk band moderate, docs partial, findings 0	Run a preview pilot with fixed ownership and observability checkpoints.	Pilot can start with rollback checklist attached.
Input: page is index-eligible	Proceed with external documentation and team onboarding draft.	Reusable rollout runbook ready for team adoption.
Input: context tags/scenarios are missing	Define two concrete scenarios before broad rollout.	Clear scope definition before further deployment.

Execution Steps

Capture objective, owner, and rollback contact.
Run one preview pilot with fixed test scenario.
Record warning behavior and recovery evidence.
Promote only if pilot output matches expected threshold.

Output Template

skill=aws-bedrock-kb-retrieval
mode=B
pilot_result=pass|fail
warning_count=0
next_step=rollout|patch|hold

🛡️ Security Analysis

SCANNED: 2026-03-14

SCORE: 80/100

✅

Clean Scan Report

Our static analysis engine detected no common vulnerabilities (RCE, API Leaks, Unbounded FS).

DocumentationREADME.md

Note: The content below is automatically rendered from the repository's README file.

AWS MCP Servers

A suite of specialized MCP servers that help you get the most out of AWS, wherever you use MCP.

AWS MCP Servers

What is the Model Context Protocol (MCP) and how does it work with AWS MCP Servers?

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

— Model Context Protocol README

An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that maintain 1:1 connections with MCP servers. Common MCP clients include agentic AI coding assistants (like Kiro, Cline, Cursor, Windsurf) as well as chatbot applications like Claude Desktop, with more clients coming soon. MCP servers can access local data sources and remote services to provide additional context that improves the generated outputs from the models.

AWS MCP Servers use this protocol to provide AI applications access to AWS documentation, contextual guidance, and best practices. Through the standardized MCP client-server architecture, AWS capabilities become an intelligent extension of your development environment or AI application.

AWS MCP servers enable enhanced cloud-native development, infrastructure management, and development workflows—making AI-assisted cloud computing more accessible and efficient.

The Model Context Protocol is an open source project run by Anthropic, PBC. and open to contributions from the entire community. For more information on MCP, you can find further documentation here

AWS MCP Servers Transport Mechanisms

Supported transport mechanisms

The MCP protocol currently defines two standard transport mechanisms for client-server communication:

stdio, communication over standard in and standard out
streamable HTTP

These AWS MCP Servers are designed to support stdio only.

You are responsible for ensuring that your use of these servers comply with the terms governing them, and any laws, rules, regulations, policies, or standards that apply to you.

Server Sent Events Support Removal

Important Notice: On May 26th, 2025, Server Sent Events (SSE) support was removed from all MCP servers in their latest major versions. This change aligns with the Model Context Protocol specification's backwards compatibility guidelines.

We are actively working towards supporting Streamable HTTP, which will provide improved transport capabilities for future versions.

For applications still requiring SSE support, please use the previous major version of the respective MCP server until you can migrate to alternative transport methods.

Why AWS MCP Servers?

MCP servers enhance the capabilities of foundation models (FMs) in several key ways:

Improved Output Quality: By providing relevant information directly in the model's context, MCP servers significantly improve model responses for specialized domains like AWS services. This approach reduces hallucinations, provides more accurate technical details, enables more precise code generation, and ensures recommendations align with current AWS best practices and service capabilities.
Access to Latest Documentation: FMs may not have knowledge of recent releases, APIs, or SDKs. MCP servers bridge this gap by pulling in up-to-date documentation, ensuring your AI assistant always works with the latest AWS capabilities.
Workflow Automation: MCP servers convert common workflows into tools that foundation models can use directly. Whether it's CDK, Terraform, or other AWS-specific workflows, these tools enable AI assistants to perform complex tasks with greater accuracy and efficiency.
Specialized Domain Knowledge: MCP servers provide deep, contextual knowledge about AWS services that might not be fully represented in foundation models' training data, enabling more accurate and helpful responses for cloud development tasks.

Available MCP Servers: Quick Installation

Get started quickly with one-click installation buttons for popular MCP clients. Click the buttons below to install servers directly in Cursor or VS Code:

🚀 Getting Started with AWS

For AWS interactions, we recommend starting with:

Server Name	Description	Install
AWS MCP Server	Start here for complete AWS interactions! This remote, managed MCP server is hosted by AWS and combines comprehensive AWS API support with access to the latest AWS documentation, API references, What's New posts, Getting Started information, and brings support for Agent standard operat

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