feat(mcpedia): Phase 1 MVP — monorepo, Core, Web UI, MCP server, Postgres FTS

- bun workspaces + Turborepo monorepo (apps/web, apps/mcp; packages/*, scripts)
- @mcpedia/core single business-logic layer (Document/Content/Search services)
- @mcpedia/db Drizzle schema: documents + weighted tsvector (GIN) for FTS
- @mcpedia/parser frontmatter, @mcpedia/search Postgres FTS (ts_rank+ts_headline)
- Next.js 16 Web UI (home/doc SSG, search dynamic) + react-markdown render
- MCP server (stdio) with 4 tools + in-memory smoke test
- scripts/indexer walks content/ -> upserts into Postgres
- 4 seed docs; README + PHASES status

packages/db/src/client.ts

@@ -0,0 +1,15 @@
+import { drizzle } from "drizzle-orm/postgres-js";
+import postgres from "postgres";
+import { DATABASE_URL } from "@mcpedia/config";
+import * as schema from "./schema";
+
+// PgBouncer (imrnes :6432) uses transaction pooling, which rejects protocol
+//-level prepared statements. prepare:false makes postgres-js use simple queries.
+const client = postgres(DATABASE_URL, {
+  prepare: false,
+  max: 5,
+  onnotice: () => {},
+});
+
+export const db = drizzle(client, { schema });
+export { schema, client };

packages/db/src/schema.ts

@@ -0,0 +1,59 @@
+import { sql, SQL } from "drizzle-orm";
+import {
+  customType,
+  index,
+  integer,
+  pgTable,
+  text,
+  timestamp,
+} from "drizzle-orm/pg-core";
+
+// tsvector isn't a first-class drizzle type; wrap the raw Postgres type.
+const tsvector = customType<{ data: string }>({
+  dataType() {
+    return "tsvector";
+  },
+});
+
+export const documents = pgTable(
+  "documents",
+  {
+    id: text("id").primaryKey(), // slug
+    slug: text("slug").notNull().unique(),
+    title: text("title").notNull(),
+    type: text("type").notNull(),
+    section: text("section").notNull(),
+    status: text("status").notNull().default("published"),
+    author: text("author").notNull().default(""),
+    tags: text("tags").array().notNull().default(sql`'{}'`),
+    path: text("path").notNull(),
+    body: text("body").notNull().default(""),
+    // Weighted search vector: title (A) + body (B), using the 'simple' config so
+    // mixed ID/EN queries match literally without stemming. Lazy closure over
+    // `documents` (must NOT reference the table eagerly — it is in TDZ here).
+    searchVector: tsvector("search_vector")
+      .notNull()
+      .generatedAlwaysAs(
+        (): SQL =>
+          sql`setweight(to_tsvector('simple', coalesce(${documents.title}, '')), 'A') || setweight(to_tsvector('simple', coalesce(${documents.body}, '')), 'B')`,
+      ),
+    createdAt: timestamp("created_at", { withTimezone: true }).notNull(),
+    updatedAt: timestamp("updated_at", { withTimezone: true }).notNull(),
+  },
+  (t) => ({
+    searchIdx: index("documents_search_idx").using("gin", t.searchVector),
+    sectionIdx: index("documents_section_idx").on(t.section),
+  }),
+);
+
+// Phase 2 (semantic search) — defined here for reference, NOT created yet:
+// export const documentChunks = pgTable("document_chunks", {
+//   id: text("id").primaryKey(),
+//   documentId: text("document_id").notNull().references(() => documents.id, { onDelete: "cascade" }),
+//   content: text("content").notNull(),
+//   position: integer("position").notNull(),
+//   embedding: customType<{ data: number[] }>({ dataType: () => "vector(1536)" })("embedding"),
+// });
+
+export type DocumentRow = typeof documents.$inferSelect;
+export type NewDocumentRow = typeof documents.$inferInsert;