feat: MCP server + in-repo skills (agent-friendly platform) (#2269)

* feat(api): support global API key from config.yaml (api.global_api_key)

Accept a config-defined global API key anywhere a web-UI key is accepted
(X-API-Key / Bearer), with no login session and no DB record. Useful for
automated deployments and AI agents (HTTP API + MCP). Defaults to empty
(disabled); does not require the lbk_ prefix.

- templates/config.yaml: add api.global_api_key with security notes
- service/apikey.py: verify_api_key checks global key first (constant-time)
- docs/API_KEY_AUTH.md: document the global key + security guidance
- tests: cover global-key match, prefix-free, fallback-to-db, disabled

* feat(mcp): expose LangBot management as an MCP server at /mcp

Add an MCP (Model Context Protocol) server so external AI agents can manage a
LangBot instance. Reuses the same API-key auth as the HTTP API (including the
config.yaml global API key).

- pkg/api/mcp/server.py: FastMCP server wrapping the service layer; 21 curated
  tools across system/bots/pipelines/models/knowledge/mcp-servers/skills
- pkg/api/mcp/mount.py: ASGI dispatcher fronting Quart; authenticates /mcp
  requests with an API key, runs the streamable-HTTP session manager lifespan
- controller/main.py: serve the wrapped ASGI app via hypercorn (was run_task)
- web: new 'MCP' tab in the API integration dialog showing endpoint, auth, and
  client config; i18n for 8 locales
- tests/manual/mcp_smoke.py: e2e check (401 unauth, list tools, call tools)

Tool surface is intentionally curated (not all ~25 route groups) to keep the
agent surface small, safe, and maintainable. Extend deliberately.

* feat(skills): add in-repo skills/ as the single source of truth

Migrate the agent skills + QA/e2e test harness from the (now archived)
langbot-app/langbot-skills repo into LangBot/skills/, and add four new skills.

Migrated:
- langbot-plugin-dev, langbot-testing (e2e), langbot-env-setup,
  langbot-skills-maintenance, langbot-eba-adapter-dev
- the bin/lbs CLI (src/, test/, scripts/, schemas/, qa-agent-docs/)

New:
- langbot-dev      core backend + web development
- langbot-deploy   Docker/K8s deployment + config.yaml + global API key
- langbot-mcp-ops  operating the LangBot MCP server (/mcp)
- langbot-space-ops operating the Space marketplace MCP server

- src/cli.ts repoRoot(): recognize the skills assets root (skills.index.json +
  bin/lbs) so the CLI works when nested inside the LangBot repo
- README.md: unified skill catalog; skills.index.json regenerated

Parity with source verified: bin/lbs validate + node test suite match the
source repo (only the uncommitted .lbpkg build-artifact fixture differs).

* docs(agents): document agent-facing surfaces + API/MCP/skills sync rule

* docs(readme): add 'Built for AI Agents' section across all locales

Highlight MCP server, in-repo skills (single source of truth), AGENTS.md
sync rule, and llms.txt. Cross-link LangBot Space MCP marketplace.

* style(mcp): fix ruff format + prettier lint in MCP server and API panel

* style(web): prettier format MCP i18n locale entries

* docs(skills): note MCP instance control in dev/testing skills

All development-guidance skills now point to the LangBot instance MCP
server (/mcp) and the Space marketplace MCP server, reusing API keys.

skills/skills/langbot-plugin-dev/references/test-env-setup.md

@@ -0,0 +1,116 @@
+# Test Environment Setup
+
+## Docker Compose (GitOps)
+
+Create in `server-deploy` repo under `servers/<hostname>/langbot-test/docker-compose.yaml`:
+
+```yaml
+version: "3"
+services:
+  langbot_plugin_runtime:
+    image: rockchin/langbot:latest
+    container_name: langbot-test-runtime
+    volumes:
+      - /opt/docker-data/langbot-test/data/plugins:/app/data/plugins
+    ports:
+      - "5411:5401"
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "rt"]
+    networks:
+      - langbot_test_network
+
+  langbot:
+    image: rockchin/langbot:latest
+    container_name: langbot-test
+    volumes:
+      - /opt/docker-data/langbot-test/data:/app/data
+    ports:
+      - "5310:5300"
+    restart: on-failure
+    depends_on:
+      - langbot_plugin_runtime
+    environment:
+      - TZ=Asia/Shanghai
+    networks:
+      - langbot_test_network
+
+networks:
+  langbot_test_network:
+    driver: bridge
+```
+
+## Post-Deploy Configuration
+
+After first start, LangBot auto-generates `data/config.yaml`. You need to update `plugin.runtime_ws_url` to match the runtime container name:
+
+```bash
+# On the host, edit config
+sed -i 's|ws://localhost:5400/control/ws|ws://langbot-test-runtime:5400/control/ws|' \
+  /opt/docker-data/langbot-test/data/config.yaml
+docker restart langbot-test
+```
+
+## Installing a Plugin
+
+Copy plugin directory to `data/plugins/` on the host:
+
+```bash
+scp -r MyPlugin/ user@host:/opt/docker-data/langbot-test/data/plugins/MyPlugin/
+docker restart langbot-test-runtime  # Runtime picks up new plugins on restart
+```
+
+## Caddy Reverse Proxy (Optional)
+
+If testing externally, add to Caddyfile on the same host:
+
+```
+langbot-test.example.com {
+    reverse_proxy langbot-test:5300
+}
+```
+
+Then reload: `docker exec caddy caddy reload --config /etc/caddy/Caddyfile`
+
+The WebSocket endpoint works through Caddy without special config.
+
+## WebSocket Test Script (Node.js)
+
+```javascript
+const WebSocket = require('ws');
+
+const PIPELINE_UUID = '<your-pipeline-uuid>';
+const BASE = 'wss://langbot-test.example.com';
+const URL = `${BASE}/api/v1/pipelines/${PIPELINE_UUID}/ws/connect?session_type=group`;
+
+const ws = new WebSocket(URL, {
+  headers: { Origin: BASE }
+});
+
+const send = (text) => {
+  ws.send(JSON.stringify({
+    type: 'message',
+    message: [{ type: 'Plain', text }]
+  }));
+  console.log('[SENT]', text);
+};
+
+ws.on('message', (data) => {
+  const msg = JSON.parse(data.toString());
+  if (msg.type === 'connected') {
+    console.log('Connected!');
+    // Send test messages
+    send('Message 1');
+    setTimeout(() => send('Message 2'), 500);
+    setTimeout(() => send('!summary'), 2000);
+  } else if (msg.type === 'response' && msg.data?.is_final) {
+    console.log('[BOT]', msg.data.content);
+  }
+});
+
+ws.on('error', (e) => console.error('Error:', e.message));
+setTimeout(() => { ws.close(); process.exit(); }, 60000);
+```
+
+Requires: `npm install ws`