sre MCP Server
SmythOS/sre
[](https://agentrank-ai.com/tool/SmythOS--sre/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime for agentic AI. Secure, modular, and production-ready, it lets developers build, run, and manage intelligent agents across local, cloud, and edge environments.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
SmythOS/sre is a TypeScript tool licensed under MIT. The SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime for agentic AI. Secure, modular, and production-ready, it lets developers build, run, and manage intelligent agents across local, cloud, and edge environments. Topics: ai, artificial-intelligence, agents, autonomous-agents, llm, mcp, multi-agent, multi-agent-systems, orchestration, rag, retrieval-augmented-generation, autogpt, chatgpt, langchain, llmops, n8n, openai, agent-framework, agi, ai-agents.
Ranked #17231 out of 24846 indexed tools.
Has 1,303 GitHub stars.
Has 23 contributors.
Ecosystem
Score Breakdown
1,303 stars → well-known project
Last commit 7mo ago → stale
4/39 issues closed → many open issues
23 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
How to Improve
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From the README
# SmythOS - The Linux of AI Agents Reliable Agent Engineering starts with great, open source infrastructure. This repository contains the **Smyth Runtime Environment** Kernel (SRE), the **Software Development Kit** (SDK) and **Command Line Interface** (CLI) for running agents and creating them with code. If you prefer visual drag & drop agent interfaces instead, check out our open source [SmythOS Visual Agent Studio](https://github.com/SmythOS/smythos-studio)! Great community, support, tutorials. Start in minutes! <br> <div align="center"> </div> <br> <div align="left"> ### SmythOS Runtime Environment (SRE) SRE is an open-source runtime and SDK for production AI agents. It provides OS-level abstractions for AI resources—LLMs, vector databases, storage, and caching—with a unified API that works identically across all providers. Write your agent logic once, scale it anywhere. Built-in security, observability, and 40+ production-ready components included. The operatRead full README on GitHub →
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