Ross ROSS = Recommend OSS · open-source software intelligence for agents

SmythOS/sre

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. observed · 2026-08-28

github.com/SmythOS/sre · homepage · TypeScript · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

52/100

  • Activity 75
  • Release rhythm 35
  • Longevity 32

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 452
  • days_rel: n/a
  • days_push: 152
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1289 stars · 201 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SmythOS Runtime Environment (SRE) is an open-source, cloud-native runtime, SDK, and CLI for building and running production AI agents across local, cloud, and edge environments. It provides OS-like abstractions over LLMs, vector databases, storage, and caching with a unified API, plus built-in security, observability, and 40+ modular components.

Use cases

  • build and deploy production AI agents in code
  • run autonomous agents locally or at the edge
  • orchestrate multi-agent workflows with a unified LLM API
  • add RAG and vector database backends to agents
  • swap LLM and storage providers without rewriting agent logic
  • self-host agent infrastructure with sandboxing and access control
  • scaffold and manage agents from the terminal

When to choose

  • you want a code-first TypeScript SDK for agent engineering rather than no-code tools
  • you need one runtime that works identically across local, cloud, and edge deployments
  • you need built-in security, credential management, and observability for agents
  • you want provider-agnostic abstractions over LLMs, vector DBs, storage, and caching

When to avoid

  • you prefer visual drag-and-drop agent building (use SmythOS Studio instead)
  • you need a lightweight single-purpose library rather than a full runtime platform
  • you want a framework with a much larger community and ecosystem like LangChain
  • your stack is not JavaScript/TypeScript

Facets

framework · maturity active

agent-framework llm-inference rag mcp sdk cli caching security monitoring workflow-automation large-language-models developer-tools self-hosted cross-platform cli self-hosted cloud agent-runtime multi-agent-systems llmops agent-orchestration cloud-native edge-deployment autonomous-agents openai langchain-alternative ai-agents retrieval-augmented-generation automation nodejs typescript docker

10 sources

Member repositories

RepositoryRoleHealth v2
SmythOS/sremain52

For agents

markdown · JSON · MCP: product_card(name="SmythOS/sre")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem