SaC — Software as Content
Give your AI agent the ability to respond with live, interactive apps that evolve.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
sac-sdkclaude mcp add sac-software-as-content -e 'SAC_API_KEY=<your sac_api_key>' -e 'SAC_API_BASE=<SAC_API_BASE>' -e 'SAC_MODEL=<SAC_MODEL>' -e 'SAC_SEARCH_API_KEY=<your sac_search_api_key>' -- uvx sac-sdk==0.1.2
{
"mcpServers": {
"sac-software-as-content": {
"command": "uvx",
"args": [
"sac-sdk==0.1.2"
],
"env": {
"SAC_API_KEY": "<your sac_api_key>",
"SAC_API_BASE": "<SAC_API_BASE>",
"SAC_MODEL": "<SAC_MODEL>",
"SAC_SEARCH_API_KEY": "<your sac_search_api_key>"
}
}
}
}
Environment variables
SAC_API_KEYrequired secret API key for the LLM provider (OpenRouter, Anthropic, OpenAI, etc.)SAC_API_BASECustom API endpoint for OpenAI-compatible providersSAC_MODELOverride the default generation modelSAC_SEARCH_API_KEYsecret Tavily API key for web search in generated apps
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
SaC SDK
Interaction layer between you and your agents.
AI agents can reason, code, and call APIs — but when they need to communicate back to you, all they have is text. SaC (Software as Content) is the missing interaction layer: your agent responds with a live, persistent, interactive app that evolves as the conversation continues. Not a screenshot, not a markdown wall — a real UI you click, explore, and shape together with your agent.
Quickstart
1. Install
pip install sac-sdk
2. Run
sac serve
First time? It'll ask for your API key and save it. Then open **http://localhost:18420**, type "3-day Tokyo trip planner with budget", and watch a live React app stream in. Click buttons. Ask it to evolve. This is SaC running a built-in agent loop — no external agent needed.
Connect to your agent
SaC plugs into the agent you already use — through MCP, Skill, or code.
Claude Code (MCP)
pip install sac-sdk
sac setup claude-code # registers SaC as an MCP server
Restart Claude Code. Then try:
"Help me understand this codebase using a visualized and interactive app using SaC MCP."
Codex (Skill)
pip install sac-sdk
sac setup codex # installs the SaC skill
sac serve # keep running in a terminal
OpenClaw (Skill)
pip install sac-sdk
sac setup openclaw # installs the SaC skill
sac serve # keep running in a terminal
Python (build your own agent)
from sac import SaC
sac = SaC()
conv = sac.conversation()
app = await conv.generate("3-day Tokyo itinerary")
print(app.url) # user opens this
# app.code contains the generated TSX
How it works
Your agent ──▶ SaC ──▶ User sees a live app at a URL
◀── User clicks a button / types a message
Your agent ──▶ SaC ──▶ Same URL, app evolves in place
◀── ...
One URL, one conversation. The agent doesn't generate a new page every turn — it evolves the existing app. Users keep their context; the agent keeps its state.
Two channels, one loop: every response is either a UI update (the app evolves) or a chat reply (a text bubble). Users can click buttons in the app OR type in the chat — both go back to the agent through the same callback.
When to use SaC
SaC is for tasks where exploration and interaction matter more than a final answer.
Good fit: trip planning, data analysis dashboards, comparison shopping, project planning, research, financial reviews, decision aids, internal tools
Not the right tool for: simple Q&A, one-shot automations ("set an alarm"), conversations that are purely text
Customize
Every layer is pluggable:
from sac import SaC, FileStore
sac = SaC(
llm=YourLLMProvider(...), # any class implementing LLMProvider
search=YourSearchProvider(...), # any class implementing SearchProvider
store=FileStore(".sac"),
)
Prompts live in src/sac/runtime/prompts/ and
the default design system is in src/sac/renderer/design-systems/default/.
Architecture
src/sac/
├── sac.py / conversation.py Entry + Conversation primitive
├── runtime/ Generate + Evolve pipeline, prompts, providers
├── server/
│ ├── http/ FastAPI + SSE streaming + viewer
│ └── mcp/ MCP stdio server (Claude Code integration)
└── renderer/ iframe sandbox + design system
Project status
v0.1.2 — alpha. The core protocol (generate → evolve → callback loop) is stable and runs in production at sac.dynsoft.ai. The SDK surface is being polished toward v1.0.
Contributing
Issues and PRs welcome. Highest-leverage contributions right now:
- Prompt improvements in
src/sac/runtime/prompts/ - Design system contributions in
src/sac/renderer/design-systems/
For local dev: pip install -e .
License
Frequently asked questions
What is SaC — Software as Content?
Give your AI agent the ability to respond with live, interactive apps that evolve.
How do I install SaC — Software as Content?
It runs on your machine. In Claude Code: claude mcp add sac-software-as-content -e 'SAC_API_KEY=<your sac_api_key>' -e 'SAC_API_BASE=<SAC_API_BASE>' -e 'SAC_MODEL=<SAC_MODEL>' -e 'SAC_SEARCH_API_KEY=<your sac_search_api_key>' -- uvx sac-sdk==0.1.2. For other clients, paste the JSON configuration from this page into their MCP settings.
Does SaC — Software as Content need an API key?
Yes. It expects SAC_API_KEY, SAC_SEARCH_API_KEY, which you set in its configuration.
Is SaC — Software as Content open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Who maintains SaC — Software as Content?
It is published by Software-As-Content. AI.tn lists it but does not maintain or endorse it.
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