mirror of https://github.com/langbot-app/LangBot.git synced 2026-07-17 01:46:07 +00:00

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T

Junyan Chin e9dd584792 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.

2026-06-20 15:14:47 +08:00

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Web UI Testing

Baseline

Read shared defaults from skills/.env.
Open LANGBOT_FRONTEND_URL.
Use LANGBOT_BACKEND_URL for backend/API/log checks.
Use Playwright MCP or another browser automation tool with a persisted authenticated profile.

Workflow

Start or verify the backend.
Start or verify the selected frontend.
Open LANGBOT_FRONTEND_URL.
Confirm the sidebar shows the logged-in user instead of the login page.
Navigate through the target flow with role/text selectors where possible.
Check browser console errors, visible UI state, and backend logs.

Browser Vs API Boundary

Use browser automation as the acceptance path for WebUI cases. API or curl checks are useful for readiness, saved config inspection, and log correlation, but they do not cover login state, form rendering, frontend save behavior, websocket streaming, or console regressions.

For a UI case, curl can support the report but cannot make the case pass by itself. A passing report should include the visible browser result and any backend/API diagnostics that explain the same run.

Authentication Notes

If the user logged in on one origin but LANGBOT_FRONTEND_URL still shows /login, copy only the auth state needed for the selected origin. Do not print token values.

Completion Signal

Report:

URL tested.
User action performed.
Visible result.
Backend or network confirmation.
Any console/backend errors that remain.

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