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GitHub
AI Infra·2023
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E2B

e2b-dev (GitHub organization)

Runs AI-generated code in secure, isolated cloud sandboxes you control via Python or JavaScript SDKs; supports self-hosting (Terraform) and AWS/GCP, enabling agents and code-interpreting workflows to execute real-world tools safely.

#python#javascript#nodejs#gitHub#aws+5
GitHub
AI Client·2024
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amazon-q-developer-cli

Amazon Web Services (AWS)

Brings an agentic chat experience to the terminal: describe a task in natural language and it plans, edits files, and runs commands to build the app. Written in Rust, ships on macOS and Linux. Now succeeded by the closed-source Kiro CLI.

#aws#cli#rust#ai#llm+5
GitHub
MCP Server·2025
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Open source MCP servers for AWS (mcp)

AWS Labs (awslabs) / Amazon Web Services·Amazon Web Services (AWS)

Exposes AWS services to AI agents over the Model Context Protocol — querying databases, provisioning infrastructure with CDK/EKS/Lambda, and pulling live AWS docs. Each domain ships as its own server, so agents wire in only what a task needs.

#mcp#mcp-server#github#ai-tools#ai-development+1
GitHub
AI Coding·2025
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AI-DLC (AI-Driven Development Life Cycle) — aidlc-workflows

AWS Labs (awslabs)

Provides adaptive workflow steering rules for AI coding agents to guide development across Inception, Construction, and Operations phases. Includes opt-in extensions (security, testing), IDE/agent integrations (Cursor, Kiro, Amazon Q, Copilot, Claude), and human-in-the-loop approval points.

#ai-workflow#aws#ai-agent#ai-coding#github+3
GitHub
AI API·2025
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Kiro Gateway

Jwadow

Exposes models available in Kiro IDE/CLI (e.g., Claude and other provider models) as local OpenAI- and Anthropic-compatible proxy endpoints so tools and SDKs can use them. Key features: multi-account failover, streaming, tool-calling, VPN/proxy support, and Docker/Python deployments.

#ai-api#anthropic#claude#aws#docker+6
GitHub
AI Agent·2026
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OpenSRE

Tracer-Cloud

Provides a framework to build, evaluate, and run AI SRE agents that investigate and remediate production incidents on your infrastructure. Includes a CLI, synthetic + end-to-end benchmark suites, and 40+ connectors for observability, infra, and LLM providers so teams can train agents and run investigations locally or in cloud.

#ai-agent#mlops#cli#github#python+4
GitHub
AI Agent·2026
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Agent Plugins for AWS

AWS Labs

Equips AI coding agents with reusable AWS skills (deployment, serverless, Amplify, SageMaker) by packaging agent skills, MCP servers, hooks, and references so agents invoke vetted workflows instead of bloating prompts.

#aws#plugin#agent-skills#mcp-server#claude-code+6
GitHub
MCP Server·2026
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Agent Toolkit for AWS

Amazon Web Services (AWS)

Provides a single MCP endpoint that lets AI coding agents search AWS docs, run sandboxed Python scripts, and make authenticated AWS API calls with enterprise guardrails like IAM condition keys, CloudWatch metrics, and CloudTrail auditing.

#aws#mcp#mcp-server#agent-skills#plugin+6
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