Add promptise

[cryxnet]

Adds promptise under AI and Agents → Orchestration in alphabetical order.

CONTRIBUTING.md compliance

Rule	Evidence
Python-first (>50% Python)	Repo is 100% Python (promptise-com/foundry)
Active (commits within 12 months)	Last push: today
Documented	Full MkDocs site at https://docs.promptise.com + README with working quickstart
Unique value	First framework in this category with a native MCP server SDK + autonomous runtime + governance + sandboxed execution as one unit — not "yet another agent library"
Established (repo ≥ 1 month)	Created 2025-08-29 (~8 months old)
PyPI display name	Uses promptise (the canonical PyPI name)
Entry format	- [pypi-name](https://github.com/owner/repo) - Description ending with period.
Category placement	AI and Agents → Orchestration, alphabetical between langchain and pydantic-ai
One short sentence	"A framework for building MCP-native agents with an autonomous runtime, governance, memory, and guardrails."
Trailing period	Yes
GitHub stars	812 (well above the 100-star bar)

Acceptance criteria

Qualifies under Rising Star — rapid growth (812 stars in ~8 months), notable community traction, and it solves a category problem in a new way: it's the first Python framework that treats MCP as a first-class server-building surface (not just a client), and ships a runtime with budgets / health / missions / secrets as built-ins.

Known caveat

The PyPI package classifier on v1.0.0 still reads Development Status :: 4 - Beta. The release itself (tagged 1.0.0, Apache-2.0, 3148 passing tests, bandit 0-HIGH) is production — the classifier is a pending metadata fix in upstream pyproject.toml that will land in the next patch. Happy to block this PR on that fix if preferred.

[arturkokurc1-prog]

pip install promptise
export OPENAI_API_KEY=sk-... # Or any supported providerimport asyncio
from promptise import build_agent

async def main():
agent = await build_agent(
model="openai:gpt-4o-mini",
instructions="You are a helpful assistant.",
)
result = await agent.ainvoke(
{"messages": [{"role": "user", "content": "Hello!"}]}
)
print(result["messages"][-1].content)
await agent.shutdown()

asyncio.run(main())