Coding & Development🤖claude🌐universal
Appstrate
[⚡️] The open‑source managed agent runtime platform.
Quick Start
Install this Skill
npx skills add appstrate/appstrate# Appstrate
[](https://github.com/appstrate/appstrate/actions/workflows/test.yml)
[](./LICENSE)
[](https://github.com/appstrate/appstrate/pkgs/container/appstrate)
[](CODE_OF_CONDUCT.md)
[](https://discord.gg/5Js2CKWNnh)
An open-source platform for running autonomous AI agents in sandboxed Docker containers. Each agent receives its full context (prompt, input, credentials) and runs to completion without human interaction — then returns structured results. Connect OAuth/API key services, click "Run" or schedule via cron, and let the AI handle the rest.

## Concepts
Appstrate uses the [AFPS](https://github.com/appstrate/afps-spec) (Agent Format Packaging Standard) packaging model. Everything is a **package** with a manifest, a version, and a scope.
```
┌───────────────────────────────┐
Goal │ Agent │ "What should the AI accomplish?"
│ prompt.md + manifest.json │ Runs autonomously in a container.
├───────────────────────────────┤
Capability │ Skill (declarative) │ Reusable instructions (SKILL.md).
│ MCP server (executable) │ Packaged MCP Bundle exposing tools.
├───────────────────────────────┤
Connection │ Integration │ OAuth 2.0, API key, basic, mTLS,
│ │ or custom auth for external services.
└───────────────────────────────┘
```
- An **agent** is the primary unit. It declares a goal (`prompt.md`), its dependencies (skills, mcp-servers, integrations), and its input/output schemas. There is no separate `config` schema: migration `0040_config_into_input` folded that second parameter namespace into `input`, leaving one. Each run creates a fresh Docker container, injects the prompt and credentials via a sidecar proxy, and produces a structured result.
- A **skill** adds knowledge — reusable instructions the agent follows during a run (`SKILL.md` + the [Anthropic Agent Skills](https://agentskills.io/) format).
- An **mcp-server** adds runnable tools. A packaged MCP Bundle (MCPB-vocabulary `server` / `tools` / `user_config`) that runs as a subprocess and speaks JSON-RPC. The agent calls its tools through the sidecar. `server.type ∈ { node, python, binary, uv }` with an optional `_meta["dev.appstrate/mcp-server"].runtime: "bun"` override for Bun-native servers.
- An **integration** adds authenticated access to an external service. Declares a `source` (local mcp-server, remote MCP endpoint, or HTTP API), one or more `auths` methods, and `delivery` for credential injection. Supports OAuth 2.0 (with RFC 8414 discovery + RFC 8707 resource indicators + PKCE), API key, basic auth, mTLS, and custom credential flows.
Agents are **prompt-driven**: the AI coding agent inside the container interprets the goal and writes its own execution code. Change the prompt, change the behavior — no node graphs, no pre-scripted steps.
## Features
- **Autonomous AI agents** — Each run executes in an isolated Docker container with a Pi Coding Agent
- **Flexible authentication** — Connect external services with OAuth 2.0 (RFC 8414 discovery + RFC 8707 resource indicators + PKCE), API key, basic auth, mTLS, and custom credential flows
- **Sandboxed runs** — Containers are created, run, and destroyed per run
- **Hardware-isolated execution** (opt-in) — Run each agent in a dedicated [Firecracker](https://firecracker-microvm.github.io/) microVM for a KVM hardware boundary around the whole run, instead of a shared-kernel container. A workload escape compromises a throwaway guest kernel, not the host. See [Firecracker architecture](./docs/architecture/FIRECRACKER.md)
- **Sidecar isolation** — Credential injection via a sidecar proxy (agent never sees raw credentials)
- **Cron scheduling** — Schedule agents with cron expressions, distributed lock prevents duplicates
- **Package import** — Import agents, skills, MCP servers, and integrations from ZIP/AFPS files
- **Skills & MCP servers** — Extend agent capabilities with SKILL.md instructions and packaged MCP Bundles (`server.type ∈ node | python | binary | uv`)
- **Realtime** — SSE-based run monitoring with LISTEN/NOTIFY
- **Multi-tenant** — Organization-based isolation with role-based access (owner/admin/member/guest), per-space membership and space roles
- **API keys** — Programmatic access via `apst_*` prefixed API keys
- **OpenAPI documentation** — every endpoint
... (truncated)Repository
20stars
1forks
Details
Related Skills
More coding & development skills you might like
Reticle
Coding & DevelopmentAI agents can generate code, but still struggle to understand what they build. Reticle brings Jev-style machine-native runtime perception to web & desktop applications.
🤖claude🌐universal
1.2k
190
View
agentscope-java
Coding & DevelopmentExpert Java developer skill for AgentScope Java framework - a reactive, message-driven multi-agent system built on Project Reactor. Use when working with reactive programming, LLM integration, agent orchestration, multi-agent systems, or when the user mentions AgentScope, ReActAgent, Mono/Flux, Project Reactor, or Java agent development. Specializes in non-blocking code, tool integration, hooks, pipelines, and production-ready agent applications.
🌐universal
6.0k
1.5k
View
ospec
Coding & DevelopmentDocument-driven OSpec workflow for initialization, change/goal routing, validation, archiving, and durable project knowledge.
✨gemini🤖claude💬gpt🌐universal
524
34
View
misakanet-failure-memory
Coding & Development📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | https://misakanet.org
🤖claude⌨️cursor🌐universal
424
158
View