MCP Servers · awslabs

mcp

AWS Labs' MCP (Model Context Protocol) is an open-source Python suite that connects AI coding assistants and agents to AWS services, documentation, and best practices. It enables tools like Claude, Cline, and Cursor to access AWS capabilities through a standardized protocol, supporting infrastructure, serverless, data, and operational workflows.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/awslabs/mcp

9.4k

GitHub stars

1.6k

Forks

Python

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	awslabs/mcp
Owner	awslabs
Primary language	Python
License	Apache-2.0 — OSI-approved
Stars	9.4k
Forks	1.6k
Open issues	836
Latest release	2026.07.20260706214220 (2026-07-06)
Last updated	2026-07-08
Source	https://github.com/awslabs/mcp

What mcp is

A collection of MCP servers written in Python that expose AWS APIs and documentation via the Model Context Protocol using stdio transport. Servers span compute, networking, databases, analytics, and cost management, integrating with LLM clients to provide context-aware AWS guidance and tool invocation capabilities.

Quickstart

Get the mcp source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/awslabs/mcp.git2cd mcp3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

AI-Assisted Infrastructure Development

Developers using Cursor, Cline, or Windsurf can invoke AWS infrastructure operations (CloudFormation, EC2, RDS) directly from their coding environment with LLM guidance, reducing context switching and deployment errors.

Autonomous Background Agents for DevOps

Background agents can monitor and manage AWS resources (CloudWatch, Cost Explorer, RDS backups) automatically, accessing real-time documentation and operational guidance without manual intervention.

Conversational AWS Knowledge Assistant

Integrate MCP servers with chatbots (Claude Desktop, custom agents) to provide contextual AWS documentation, best practices, and cost optimization recommendations during development or operational discussions.

Implementation considerations

Requires Python environment and AWS credentials (IAM keys or STS tokens) to be securely configured on the host where MCP servers run; ensure least-privilege IAM policies are applied.
Only stdio transport is currently supported; HTTP-based clients or remote-deployed servers require wrapping (e.g., AWS Lambda module mentioned in README; Streamable HTTP support is in development).
MCP server versions recently removed SSE support (May 2025); verify client compatibility with current stdio-only versions before upgrading to avoid breaking changes.
Spans 20+ specialized servers (EC2, RDS, S3, Lambda, DynamoDB, Cost Explorer, etc.); you need to selectively enable only required servers to reduce memory footprint and attack surface.
Integrates with non-AWS tooling (Cursor, Cline, Claude, VS Code); test integration in your specific IDE/client before deploying to production workflows.

When to avoid it — and what to weigh

Production-Critical Compliance Workflows — The README explicitly notes this is open-source labs code. AWS recommends the paid 'Agent Toolkit for AWS' for production use, which includes IAM distinction, CloudTrail visibility, and accuracy validation—not present here.
Strict Real-Time Determinism Required — MCP servers are designed for conversational or batch workflows; they depend on LLM reasoning and are not suitable for time-critical, deterministic operations requiring <100ms latency.
Air-Gapped or Offline Environments — Servers require live AWS API access and documentation retrieval; they cannot operate fully offline. Remote deployment in restricted networks may face connectivity or authentication challenges.
Non-AWS Cloud or Hybrid Multi-Cloud — Scope is AWS-only. If you run multi-cloud (Azure, GCP) or on-prem infrastructure, this suite provides no native support for those platforms.

License & commercial use

Apache License 2.0 (Apache-2.0). Permissive OSI-approved license allowing commercial use, modification, and distribution with attribution and no warranty/liability.

Apache-2.0 permits commercial use. However, AWS Labs explicitly recommends the paid 'Agent Toolkit for AWS' for production environments (noted in README). This repo is community-maintained labs code; use only after risk assessment for non-trivial deployments. Ensure your use complies with AWS service terms and any applicable laws/regulations.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

AWS credentials are passed to MCP servers; ensure they run in trusted environments and are not exposed to untrusted users. No explicit mention of encryption in transit (stdio is unencrypted by default; wrap with TLS if needed). IAM policies should be least-privilege; MCP servers inherit all permissions of the credentials provided. README includes Security section (not detailed in excerpt); review full repo for vulnerability disclosure policy and known issues.

Alternatives to consider

AWS Agent Toolkit (paid)

Official AWS successor with IAM condition keys, CloudTrail/CloudWatch visibility, and validated accuracy. Recommended for production by AWS Labs themselves.

Anthropic's MCP Protocol + Custom Servers

Use the open MCP spec to build custom servers for your specific AWS workflows, avoiding the breadth and overhead of 20+ pre-built servers.

AWS SDKs (boto3, AWS CLI) + Direct LLM Integration

Simpler for deterministic workflows; skip MCP protocol layer if you control the LLM and only need programmatic AWS access without conversational context.

Software development agency

Build on mcp with DEV.co software developers

Start with the quickstart guides for Cursor, Cline, or VS Code. Evaluate against AWS Agent Toolkit for production. Review security and IAM policies before deploying.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

elevenlabs-mcp servers mcpc

Related on DEV.co

Explore the category and the services that help you build with it.

MCP Servers AI Application Development Cloud Deployment DevOps Talk to DEV.co

mcp FAQ

Can I use this in production?

AWS Labs recommends the paid Agent Toolkit for AWS for production. This repo is open-source and community-maintained; use only after thorough testing and risk acceptance.

What if my MCP client doesn't support stdio?

Current servers support stdio only. An AWS Lambda handler module is mentioned; review the repo for details. HTTP transport (Streamable HTTP) is in development.

Do I need to install all 20+ MCP servers?

No. Install only the servers you need (e.g., EC2, S3, Lambda for infrastructure work). Each server is independent.

How are AWS credentials handled?

MCP servers use your AWS SDK credentials (environment variables, ~/.aws/credentials, IAM roles). Apply least-privilege IAM policies. Credentials are not encrypted in stdio transport by default.

Software development & web development with DEV.co

DEV.co helps companies turn open-source tools like mcp into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your mcp servers stack.

Ready to integrate AWS into your AI coding workflow?

Start with the quickstart guides for Cursor, Cline, or VS Code. Evaluate against AWS Agent Toolkit for production. Review security and IAM policies before deploying.

Talk to DEV.co Schedule a Consultation