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Hongming Wang 70d66cd814 feat: poll-mode inbound delivery + molecule connect CLI (Phase 30.8c)
External agents that can't expose a public HTTP endpoint (laptops behind
NAT, ephemeral CI runners, hermes self-hosted, codex et al) had to reverse-
engineer the activity-poll loop from molecule-mcp-claude-channel/server.ts
because the SDK only shipped the push-mode `A2AServer` (Phase 30.8b).

This adds the complementary path:

- `RemoteAgentClient.fetch_inbound(since_id=…)` — one-shot GET against
  `/workspaces/:id/activity?type=a2a_receive&since_id=…`. Cursor-loss (410)
  surfaces as `CursorLostError`; caller resets and re-polls.
- `RemoteAgentClient.reply(msg, text)` — smart-routes to `/notify` for
  canvas users, `/a2a` (JSON-RPC envelope + X-Source-Workspace-Id) for peer
  agents. Hides the reply-path bifurcation from connector authors.
- `PollDelivery` / `PushDelivery` / `InboundDelivery` protocol — same
  `MessageHandler` callback works for both transports.
- `RemoteAgentClient.run_agent_loop(handler, delivery=None)` — combined
  heartbeat + state-poll + inbound dispatch. Defaults to `PollDelivery`.
  Async handlers detected and `asyncio.run`'d (matches A2AServer pattern).
  Sleep cadence = min(heartbeat_interval, delivery.interval).
- `python -m molecule_agent connect` CLI — one-line bootstrap. Loads a
  user's `module:function` via importlib, registers, runs the loop until
  pause/delete or SIGTERM. All flags also read from environment variables.

Tests: 50 new (test_inbound.py, test_cli_connect.py) covering every prod
branch — source normalization, cursor advancement, 410 reset, async/sync
handler dispatch, handler exception → log+continue+advance, smart-reply
routing for canvas vs peer vs unknown sources, run_agent_loop terminal
states, sleep-interval selection, CLI handler resolution failures.

Resolves #17.
2026-04-30 13:03:44 -07:00
.claude docs: add CLAUDE.md, known-issues.md, and .claude/settings.json (#2) 2026-04-20 23:10:37 +00:00
.github/workflows Merge pull request #13 from Molecule-AI/gap-03-fix 2026-04-24 13:27:24 -07:00
examples/remote-agent feat: initial Python SDK (extracted from molecule-monorepo/sdk/python) 2026-04-16 03:15:38 -07:00
molecule_agent feat: poll-mode inbound delivery + molecule connect CLI (Phase 30.8c) 2026-04-30 13:03:44 -07:00
molecule_plugin fix(lint): remove unused typing.Any import (ruff F401) 2026-04-23 22:15:51 +00:00
template feat: initial Python SDK (extracted from molecule-monorepo/sdk/python) 2026-04-16 03:15:38 -07:00
tests feat: poll-mode inbound delivery + molecule connect CLI (Phase 30.8c) 2026-04-30 13:03:44 -07:00
.DS_Store feat: initial Python SDK (extracted from molecule-monorepo/sdk/python) 2026-04-16 03:15:38 -07:00
.gitignore chore: gitignore credentials for molecule-sdk-python 2026-04-16 09:19:08 -07:00
CLAUDE.md feat: poll-mode inbound delivery + molecule connect CLI (Phase 30.8c) 2026-04-30 13:03:44 -07:00
known-issues.md docs(sdk): update known-issues.md — mark KI-003 resolved, KI-008 resolved 2026-04-21 22:04:44 +00:00
pr-description-draft.md feat(security): add plugin content integrity verification (SHA256) (#3) 2026-04-21 01:00:35 +00:00
pyproject.toml fix(pyproject): point PyPI URLs at the actual SDK repo 2026-04-26 12:07:51 -07:00
pytest.ini feat: initial Python SDK (extracted from molecule-monorepo/sdk/python) 2026-04-16 03:15:38 -07:00
README.md feat: initial Python SDK (extracted from molecule-monorepo/sdk/python) 2026-04-16 03:15:38 -07:00

molecule_plugin — Python SDK for building Molecule AI plugins

A Molecule AI plugin is a directory that bundles rules, skills, and per-runtime install adaptors. Any plugin that conforms to this contract is installable on any Molecule AI workspace whose runtime the plugin supports.

Quick start

Copy template/ to a new directory and edit:

my-plugin/
├── plugin.yaml              # name, version, runtimes, description
├── rules/my-rule.md         # optional — appended to CLAUDE.md at install
├── skills/my-skill/
│   ├── SKILL.md             # instructions injected into the system prompt
│   └── tools/do_thing.py    # optional LangChain @tool functions
└── adapters/
    ├── claude_code.py       # one-liner: `from molecule_plugin import AgentskillsAdaptor as Adaptor`
    └── deepagents.py        # same

Validate:

from molecule_plugin import validate_manifest
errors = validate_manifest("my-plugin/plugin.yaml")
assert not errors, errors

CLI

The SDK ships a CLI for validating Molecule AI artifacts before publishing:

python -m molecule_plugin validate plugin    my-plugin/
python -m molecule_plugin validate workspace workspace-configs-templates/claude-code-default/
python -m molecule_plugin validate org       org-templates/molecule-dev/
python -m molecule_plugin validate channel   channels.yaml
python -m molecule_plugin validate my-plugin/   # kind defaults to 'plugin'

Exit code is 0 when valid, 1 when any errors are found — suitable for CI. Add -q / --quiet to suppress success lines and emit only errors.

Programmatic equivalents:

from molecule_plugin import (
    validate_plugin,
    validate_workspace_template,
    validate_org_template,
    validate_channel_file,
    validate_channel_config,
)

Per-runtime adaptors — when to write a custom one

The default AgentskillsAdaptor handles the common shape: rules go into the runtime's memory file (CLAUDE.md), skill dirs go into /configs/skills/. That covers most plugins.

Write a custom adaptor when you need to:

  • Register runtime tools dynamically — call ctx.register_tool(name, fn).
  • Register DeepAgents sub-agents — call ctx.register_subagent(name, spec).
  • Write to a non-standard memory file — call ctx.append_to_memory(filename, content).

Minimum custom adaptor:

# adapters/deepagents.py
from molecule_plugin import InstallContext, InstallResult

class Adaptor:
    def __init__(self, plugin_name: str, runtime: str):
        self.plugin_name, self.runtime = plugin_name, runtime

    async def install(self, ctx: InstallContext) -> InstallResult:
        ctx.register_subagent("my-agent", {"prompt": "...", "tools": [...]})
        return InstallResult(plugin_name=self.plugin_name, runtime=self.runtime, source="plugin")

    async def uninstall(self, ctx: InstallContext) -> None:
        pass

Resolution order (understood by the platform)

For (plugin_name, runtime):

  1. Platform registryworkspace-template/plugins_registry/<plugin>/<runtime>.py (curated; set by the Molecule AI team for quality-assured plugins).
  2. Plugin-shipped<plugin_root>/adapters/<runtime>.py (what this SDK helps you build).
  3. Raw-drop fallback — copies plugin files into /configs/plugins/<name>/ and surfaces a warning; no tools are wired.

You generally ship for path #2. If your plugin becomes popular enough to be promoted to "default," the Molecule AI team PRs a copy of your adaptor into the platform registry (path #1) so it survives upstream breakage.

Testing locally

The SDK ships AgentskillsAdaptor as a standalone, unit-testable class:

import asyncio
from pathlib import Path
from molecule_plugin import AgentskillsAdaptor, InstallContext

ctx = InstallContext(
    configs_dir=Path("/tmp/configs"),
    workspace_id="local",
    runtime="claude_code",
    plugin_root=Path("./my-plugin"),
)
asyncio.run(AgentskillsAdaptor("my-plugin", "claude_code").install(ctx))
# check /tmp/configs/CLAUDE.md, /tmp/configs/skills/

Publishing

A plugin is just a directory. Push it to any Git host. Installation via POST /plugins/install {git_url} is on the roadmap — see the platform's PLAN.md under "Install-from-GitHub-URL flow." Until then, plugins are bundled into the platform by dropping them into plugins/ at deploy time.

Supported runtimes

As of 2026-Q2: claude_code, deepagents, langgraph, crewai, autogen, openclaw. See the live list with:

curl $PLATFORM_URL/plugins