i-am-bee/agentstack
Deploy, and share agents with open infrastructure, free from vendor lock-in. observed · 2026-08-28
Health v2 · maintenance only
80/100
- Activity 99
- Release rhythm 77
- Longevity 41
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 12
- age_days: 583
- days_rel: 156
- days_push: 7
- n_releases_24m: 20
Adoption not part of the score
1149 stars · 185 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Agent Stack is open-source infrastructure (hosted by the Linux Foundation) for turning AI agents into running HTTP services, built on the Agent2Agent (A2A) Protocol. It bundles an agent runtime, LLM routing across 15+ providers, vector storage, authentication, S3-compatible file storage, a CLI, a web UI, and a Kubernetes Helm chart so agents can move from local development to production without rewrites.
Use cases
- deploy ai agents as backend services
- run agents locally while developing then ship to production
- self-host an agent runtime without vendor lock-in
- expose langgraph or crewai agents over http via a2a
- add llm routing and vector search to my agent app
- manage agent secrets and oauth integrations with slack or google drive
- build a custom chat ui for my agents with a typed sdk
When to choose
- you want to run agents as production services without building deployment infrastructure yourself
- you need framework-agnostic agent hosting (LangGraph, CrewAI, custom code)
- you want an open, A2A-compatible, self-hostable alternative to proprietary agent platforms
- you need built-in LLM provider routing, embeddings, file storage, and secrets management
When to avoid
- you only need a lightweight agent library inside a single app with no service deployment
- you want a fully managed hosted platform rather than self-hosting a VM/Kubernetes stack
- your environment cannot run Lima/QEMU VMs or Kubernetes locally
- you need a mature, long-proven product - the project is young and Windows support is experimental
Facets
framework · maturity active
agent-framework llm-inference rag deployment cli secrets-management file-upload mcp large-language-models developer-tools self-hosted infrastructure-as-code windows python cli self-hosted a2a-protocol agent-deployment agent-runtime llm-routing vector-storage helm-chart linux-foundation beeai ai-agents linux macos docker kubernetes
4 sources
- readme: https://github.com/i-am-bee/agentstack · fetched 2026-08-28 · 08d1540d3a28
- homepage: https://agentstack.beeai.dev · fetched 2026-08-29 · 758ac4934d4b
- site_page: https://agentstack.beeai.dev/stable/introduction/quickstart · fetched 2026-08-29 · 64c82b8966e7
- site_page: https://agentstack.beeai.dev/stable/custom-ui/getting-started · fetched 2026-08-29 · 920c283c4bc4
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| i-am-bee/agentstack | main | 80 |
For agents
markdown · JSON · MCP: product_card(name="i-am-bee/agentstack")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem