mirror of https://github.com/langbot-app/LangBot.git synced 2026-06-23 14:04:19 +00:00

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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

4.6 KiB

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日志守卫规划

状态

这是当前活跃设计，已有第一版文件扫描 MVP。实现边界需要和黑盒 E2E 路线保持一致：

日志守卫服务于 lbs test report。
它不替代浏览器/UI 判断。
它不发展成独立后端 API 测试框架。
第一版默认扫描 LANGBOT_REPO/data/logs/ 下最新的 langbot-*.log，也可扫描 agent 显式提供的 backend/frontend/console 日志文件。

当前总体路线见：

docs/qa-agent/04-black-box-e2e-roadmap.md

目标

日志守卫是 lbs test report 的一部分，用来在 agent 执行测试期间捕获 UI 断言之外的运行时问题。

当前命令方向已收敛为 lbs test plan / lbs test report。日志守卫服务于 agent-browser QA，不是独立的后端 API 测试入口。

LangBot 是异步且集成度高的系统，有些问题不会直接表现为页面失败：

后台任务异常
未等待的协程
Provider 流式调用失败
插件 runtime 超时
平台发送失败
数据库连接问题
敏感信息泄露

日志守卫负责把这些信号结构化地放进测试报告，并关联到 troubleshooting 资产。

输入

日志守卫应从环境和运行上下文读取配置：

skills/.env 中的 LANGBOT_BACKEND_URL
skills/.env 中的 LANGBOT_REPO，用于自动发现 LangBot 后端日志
lbs test plan / report 记录的 case id
LangBot 后端进程输出
前端 dev server 输出
浏览器 console/network 错误
case 声明的 success/failure patterns 和 expected failures

MVP 范围

读取一个或多个日志流或日志文件。
检测错误模式。
支持按 case id 或 pattern 白名单。
输出 JSON/Markdown 摘要。
发现非预期错误时让测试报告标记失败；未来如果有自动执行器，再返回非零退出码。

错误分类

永远非预期

除非 case 明确声明，否则应失败：

Traceback
Task exception was never retrieved
RuntimeWarning: coroutine .* was never awaited
Unclosed client session
Unclosed connector
KeyError
TypeError
AttributeError
密钥、token、secret 明文泄露

Case 预期错误

只有当前 case 声明时允许：

无效 provider key
Provider 认证失败
无效 webhook payload
插件测试故意抛错
超时测试
限流测试

仅警告

报告但默认不失败：

可恢复重试
恢复的超时
废弃配置
慢请求
版本检查失败

与 Troubleshooting 集成

日志守卫不只输出错误文本，还应尽量匹配已知 troubleshooting id。

例子：

Action list_plugins call timed out
Action list_agent_runners call timed out
Action invoke_llm_stream call timed out

可映射到：

plugin-runtime-timeout

uppercase proxy points to one host, lowercase proxy points to another

可映射到：

proxy-env-mismatch

未来命令

bin/lbs test plan pipeline-debug-chat
bin/lbs test start pipeline-debug-chat
bin/lbs test run pipeline-debug-chat --dry-run
bin/lbs test report pipeline-debug-chat
bin/lbs test report --output report.md
bin/lbs test report pipeline-debug-chat --backend-log /path/to/backend.log --console-log /path/to/console.log
bin/lbs test report pipeline-debug-chat --since "2026-05-21T10:30:00+08:00"
bin/lbs test report pipeline-debug-chat --tail-lines 2000
bin/lbs test report pipeline-debug-chat --since "2026-05-21T10:30:00+08:00" --tail-lines 2000
bin/lbs test report pipeline-debug-chat --no-auto-log

运行报告应包含：

case id
URL 和环境变量摘要，不能包含 secrets
浏览器可见结果
后端日志摘要
console/network 错误
匹配到的 troubleshooting id
通过/失败结论

MVP 完成标准

可以自动扫描最新 LangBot 后端日志，也可以扫描前端日志和 console 日志文件。
可以用 --since 或 --tail-lines 把扫描范围限制到本次测试窗口。
可以检测明显 Python/运行时错误和 secret 泄露风险。
可以识别 case 声明的 success/failure patterns。
可以识别 troubleshooting pattern，包括 plugin-runtime-timeout 和 proxy-env-mismatch。
支持 case 级白名单。
输出机器可读摘要。
至少一个 langbot-testing case 使用它。

当前 MVP 已覆盖自动发现 LangBot 后端日志、文件扫描、--since/--tail-lines 扫描窗口、基础错误检测、case success/failure signal、troubleshooting 匹配、secret 脱敏和 --json 输出。仍待继续完善的是 live log 采集、更多规则、case 级 expected failure 的资产化和真实 E2E report 样例。

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