No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by awslabs · MCP Server · ★ 378
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is run-model-context-protocol-servers-with-aws-lambda safe to install? View the security audit →
Run Model Context Protocol (MCP) servers with AWS Lambda This project enables you to run Model Context Protocol stdio-based servers in AWS Lambda functions. Currently, most implementations of MCP servers and clients are entirely local on a single machine. A desktop application such as an IDE or Claude Desktop initiates MCP servers locally as child processes and communicates with each of those servers over a long-running stdio stream. This library helps you to wrap existing stdio MCP servers into Lambda functions. You can invoke these function-based MCP servers from your application using the MCP protocol over short-lived HTTPS connections. Your application can then be a desktop-based app, a distributed syst
| Stars | 378 |
| Forks | 46 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.2784422954558/100 |
| Open Issues | 17 |
| Last Updated | 2026-08-12 |
| Created | 2025-03-21 |
| Platforms | aws, mcp, python |
| Est. Tokens | ~19k |
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run-model-context-protocol-servers-with-aws-lambda is Run existing Model Context Protocol (MCP) stdio-based servers in AWS Lambda functions. It is categorized as a MCP Server with 378 GitHub stars.
run-model-context-protocol-servers-with-aws-lambda is primarily written in Python.
You can find installation instructions and usage details in the run-model-context-protocol-servers-with-aws-lambda GitHub repository at github.com/awslabs/run-model-context-protocol-servers-with-aws-lambda. The project has 378 stars and 46 forks, indicating an active community.
run-model-context-protocol-servers-with-aws-lambda is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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