AWS MCP

Created By
RafalWilinskia year ago
Talk with your AWS using Claude. Model Context Protocol (MCP) server for AWS. Better Amazon Q alternative.
Overview

what is AWS MCP?

AWS MCP (Model Context Protocol) is a server that enables AI assistants like Claude to interact seamlessly with your AWS environment, facilitating natural language querying and management of AWS resources as a better alternative to Amazon Q.

how to use AWS MCP?

To use AWS MCP, clone the repository, install the dependencies, configure the Claude desktop app by adding the MCP server settings, and then you can start querying AWS resources via natural language commands.

key features of AWS MCP?

  • Natural language querying and modification of AWS resources
  • Support for multiple AWS profiles and Single Sign-On (SSO) authentication
  • Multi-region support for AWS services
  • Secure credential handling, using local AWS credentials without exposing them externally
  • Local execution with seamless integration using AWS credentials

use cases of AWS MCP?

  1. Querying details of EC2 instances in a user's AWS account.
  2. Listing S3 buckets and their sizes easily via natural language.
  3. Managing multiple AWS profiles and accessing resources across different regions.

FAQ from AWS MCP?

  • Can AWS MCP work with various AWS services?

Yes! AWS MCP can interact with multiple AWS services like EC2, S3, Lambda, and ECS using simple queries.

  • Do I need special permissions to use AWS MCP?

Yes, you will need proper AWS credentials configured locally to access your resources.

  • Is there ongoing development for new features?

Yes! Features in development include MFA support and caching SSO credentials.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
RafalWilinski
Star
140
Language
TypeScript
License
-
Tags

Recommend Servers

View All
Achivx Forum

2 hours ago
Origine Paris Mcp

17 hours ago
Thiri Chord Intelligence
@BluesPrince

### Deterministic Music Theory for Claude, Cursor, and Autonomous AI Agents Large Language Models (LLMs) frequently hallucinate music theory, leading to incorrect notes, false Roman numerals, and broken voice leading. **THIRI** solves this by providing a deterministic, mathematical music-theory engine (pitch-class-set theory over ℤ/12) directly to your AI. It gives AI assistants precise, reproducible harmonic reasoning in milliseconds, allowing them to write correct musical scores, analyze progressions, and generate playable arrangements. #### 🎷 Key Features: * **Chord Analysis (`analyze_chord`):** Parse any symbol (e.g., `Cmaj7/E`, `G7#11`) to retrieve root, quality, intervals, Roman numerals, and diatonic or chromatic harmonic functions. * **Note Resolution (`resolve_chord`):** Resolve chord symbols to spelled notes (enharmonically correct), frequencies (Hz), MIDI numbers, and scale recommendations. * **Voicing Engine (`generate_voicing`):** Generate instrument-ready voicings (rootless, shell, triad, pad, drop-2, drop-3) and calculate voice-leading scores for transitions. * **Reharmonization (`reharmonize`):** Substitute progressions using classic jazz techniques, including Tritone Substitution, ii-V Insertion, Modal Interchange, Coltrane Changes, and Backdoor cadences. *Ideal for developers building AI music assistants, digital audio workstation (DAW) agents, educational theory tools, and automated composition workflows.*

11 hours ago