mirror of
https://github.com/langbot-app/LangBot.git
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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.
This commit is contained in:
Junyan Chin
@@ -0,0 +1,180 @@
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import { existsSync, mkdirSync, writeFileSync } from "node:fs";
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import { join, resolve } from "node:path";
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import type { CommandContext } from "../types.ts";
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import { parseOptions, optionString, usage, fail } from "../cli.ts";
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import { caseModeValues } from "../constants.ts";
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import { boolValue, findStructuredItem, getSkill, listValue, loadStructuredItems, scalar, yamlList, yamlQuote } from "../fs.ts";
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import { caseAutomationReadiness, caseEnvReadiness, caseFixtureReadiness, caseManualReadiness, runtimeEnv } from "../readiness.ts";
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import { setupAutomationEntries } from "../setup-automation.ts";
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function casePath(root: string, skillName: string, id: string): string {
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const skill = getSkill(root, skillName);
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const dir = join(skill.path, "cases");
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mkdirSync(dir, { recursive: true });
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return join(dir, `${id}.yaml`);
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}
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export function commandCaseNew(ctx: CommandContext): number {
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const { positional, options } = parseOptions(ctx.args.slice(2));
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const id = positional[0];
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const title = optionString(options, "title");
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if (!id || !title) usage();
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const skill = optionString(options, "skill") ?? "langbot-testing";
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const path = casePath(ctx.root, skill, id);
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if (existsSync(path)) fail(`case already exists: ${path}`);
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const area = optionString(options, "area") ?? "general";
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const type = optionString(options, "type") ?? "smoke";
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const mode = optionString(options, "mode") ?? "agent-browser";
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if (!caseModeValues.includes(mode)) fail(`--mode must be one of ${caseModeValues.join(", ")}`);
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const isProbe = mode === "probe";
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const text =
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`id: ${id}\n` +
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`title: ${yamlQuote(title)}\n` +
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`mode: ${mode}\n` +
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`area: ${area}\n` +
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`type: ${type}\n` +
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"priority: p2\n" +
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"risk: medium\n" +
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"ci_eligible: false\n" +
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"tags:\n" +
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yamlList([type]) +
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"\nskills:\n" +
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yamlList(["langbot-env-setup", skill]) +
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"\nenv:\n" +
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yamlList(isProbe ? [] : ["LANGBOT_FRONTEND_URL", "LANGBOT_BACKEND_URL"]) +
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"\nsteps:\n" +
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yamlList([isProbe ? "Describe the probe command, script, or diagnostic to run." : "Describe the user-visible action to perform."]) +
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"\nchecks:\n" +
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yamlList(isProbe
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? [
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"Probe: Describe the expected success signal.",
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"Evidence: Required logs, API diagnostics, or filesystem artifacts are written.",
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]
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: [
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"UI: Describe the user-visible success signal.",
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"Console: No unexpected frontend errors.",
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"Logs: Relevant backend processing completed when applicable.",
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]) +
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"\nevidence_required:\n" +
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yamlList(isProbe ? ["api_diagnostic"] : ["ui", "console"]) +
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"\ndiagnostics:\n" +
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yamlList([isProbe
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? "Use logs, API, or filesystem diagnostics to explain probe failures."
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: "Use API/curl/logs only to distinguish frontend failure from backend/runtime failure."]) +
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"\ntroubleshooting:\n" +
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yamlList([]) +
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"\n";
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writeFileSync(path, text, "utf8");
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console.log(path);
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return 0;
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}
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function caseRow(item: ReturnType<typeof loadStructuredItems>[number], root: string): Record<string, unknown> {
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const automation = scalar(item.fields, "automation");
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const env = runtimeEnv(root);
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const id = scalar(item.fields, "id");
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const row = {
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skill: item.skill,
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id,
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title: scalar(item.fields, "title"),
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mode: scalar(item.fields, "mode"),
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area: scalar(item.fields, "area"),
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type: scalar(item.fields, "type"),
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priority: scalar(item.fields, "priority"),
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risk: scalar(item.fields, "risk"),
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ci_eligible: boolValue(item.fields, "ci_eligible") ?? false,
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tags: listValue(item.fields, "tags"),
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env: listValue(item.fields, "env"),
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env_any: listValue(item.fields, "env_any"),
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preconditions: listValue(item.fields, "preconditions"),
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setup: listValue(item.fields, "setup"),
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setup_automation: setupAutomationEntries(item),
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setup_provides_env: listValue(item.fields, "setup_provides_env"),
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cleanup: listValue(item.fields, "cleanup"),
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evidence_required: listValue(item.fields, "evidence_required"),
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automation,
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automation_exists: automation ? existsSync(resolve(root, automation)) : false,
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env_readiness: caseEnvReadiness(item, env),
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automation_readiness: caseAutomationReadiness(item, env),
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fixture_readiness: caseFixtureReadiness(root, id),
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manual_readiness: caseManualReadiness(item),
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};
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return {
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...row,
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readiness: readinessLabel(row),
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};
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}
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function hasTag(row: Record<string, unknown>, tag: string): boolean {
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const tags = row.tags;
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return Array.isArray(tags) && tags.includes(tag);
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}
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function hasMissingReadiness(row: Record<string, unknown>): boolean {
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for (const key of ["env_readiness", "automation_readiness", "fixture_readiness"]) {
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const value = row[key] as Record<string, unknown> | undefined;
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if (value?.status === "missing") return true;
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}
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return false;
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}
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function hasManualCheck(row: Record<string, unknown>): boolean {
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const manual = row.manual_readiness as Record<string, unknown> | undefined;
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return manual?.status === "manual_check";
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}
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function readinessLabel(row: Record<string, unknown>): string {
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if (hasMissingReadiness(row)) return "not-ready";
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return hasManualCheck(row) ? "manual-check" : "ready";
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}
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export function commandCaseList(ctx: CommandContext): number {
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const { positional, options } = parseOptions(ctx.args.slice(2));
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const skill = positional[0];
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const rows = loadStructuredItems(ctx.root, "cases", skill)
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.map((item) => caseRow(item, ctx.root))
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.filter((row) => !optionString(options, "type") || row.type === optionString(options, "type"))
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.filter((row) => !optionString(options, "area") || row.area === optionString(options, "area"))
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.filter((row) => !optionString(options, "priority") || row.priority === optionString(options, "priority"))
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.filter((row) => !optionString(options, "risk") || row.risk === optionString(options, "risk"))
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.filter((row) => !optionString(options, "tag") || hasTag(row, optionString(options, "tag") ?? ""))
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.filter((row) => options.automation !== true || Boolean(row.automation))
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.filter((row) => options.ci !== true || row.ci_eligible === true)
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.filter((row) => options["machine-ready"] !== true || !hasMissingReadiness(row))
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.filter((row) => options.ready !== true || (!hasMissingReadiness(row) && !hasManualCheck(row)));
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if (options.json === true) {
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console.log(JSON.stringify(rows, null, 2));
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return 0;
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}
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for (const row of rows) {
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console.log([
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row.skill,
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row.id,
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row.type,
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row.area,
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row.priority,
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row.risk,
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row.ci_eligible ? "ci" : "manual",
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row.automation ? "automated" : "manual-path",
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row.readiness,
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row.title,
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].join("\t"));
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}
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return 0;
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}
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export function commandCaseShow(ctx: CommandContext): number {
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const positional = ctx.args.slice(2);
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if (positional.length < 1 || positional.length > 2) usage();
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const item = positional.length === 1
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? findStructuredItem(ctx.root, "cases", positional[0])
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: findStructuredItem(ctx.root, "cases", positional[0], positional[1]);
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console.log(item.raw.trimEnd());
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return 0;
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}
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