asepharyana
9397303f01
- @mcpedia/embeddings: OpenRouter provider (9router /v1, encoding_format float), chunkText + embedChunks; EMBED_DIM=2048 - document_chunks table (real[] embedding) — pgvector NOT available on shared imrnes Postgres, so cosine is computed in-app (KB-scale fine); pgvector deferred - indexer: chunk + embed + upsert per document - @mcpedia/search: semanticSearch (cosine) + hybridSearch (FTS+cosine RRF) - apps/api: Hono + tRPC v11 (6 procedures), serve on :4020 - MCP: semantic_search + hybrid_search tools (6 total) - web: keyword/hybrid toggle; .env.example + README + PHASES updated
136 lines
4.9 KiB
Markdown
136 lines
4.9 KiB
Markdown
# MCPedia
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> A content-first knowledge base — readable as Markdown/MDX in Git, queryable by
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> humans via a Web UI and by AI agents via the Model Context Protocol (MCP).
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MCPedia keeps content as plain Markdown files under `content/`. A Git-tracked
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source of truth, indexed into PostgreSQL (metadata + a `tsvector` full-text
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column) and served through a single **Core** layer that every interface
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(Web, MCP) shares — no business logic duplicated per surface.
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## Monorepo layout
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```
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mcpedia/
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├── apps/
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│ ├── web/ # Next.js 16 (Turbopack) — human-facing docs UI + search
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│ └── mcp/ # MCP server (stdio) — AI-agent interface
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├── packages/
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│ ├── types/ # shared domain types (DocSection, Document, SearchHit, ...)
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│ ├── config/ # loads .env (repo root) as authoritative dev config
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│ ├── db/ # Drizzle ORM schema + client + drizzle-kit config
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│ ├── parser/ # frontmatter (gray-matter) parsing
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│ ├── search/ # Postgres FTS query (ts_rank + ts_headline)
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│ └── core/ # Document/Content/Search services — the only business logic
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├── content/ # docs/ writeups/ research/ notes/ (the knowledge base)
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└── scripts/ # indexer.ts (walks content/ -> upserts into Postgres)
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```
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## Architecture principle
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```
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Web ─┐
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├──► Core ──► Repository (@mcpedia/db) ──► PostgreSQL
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MCP ─┘
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```
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All interfaces go through `@mcpedia/core`. Nothing outside `packages/db` and
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`packages/core` touches the database directly.
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## Quick start
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```bash
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bun install # install workspace deps
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cp .env.example .env # set DATABASE_URL (dev uses imrnes Postgres :6432)
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bunx turbo run build # typecheck + build every package
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bun run index # walk content/ -> upsert into Postgres
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bun --cwd apps/web run dev # Web UI on :3000
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bun run mcp # MCP server on stdio (pipe to an MCP client)
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```
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### Database
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Schema is defined in `packages/db/src/schema.ts` (`documents` with a weighted
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`search_vector` tsvector + GIN index, and `document_chunks` with an `embedding real[]`).
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The `pgvector` extension is **not available** on the shared imrnes Postgres, so
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semantic search stores vectors as `real[]` and ranks by in-app cosine similarity.
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Migrations live in `packages/db/drizzle/`. They were applied manually via `psql`
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(`drizzle-kit push` is unreliable under PgBouncer transaction pooling); to
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re-apply on a fresh DB:
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```bash
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psql $DATABASE_URL -f packages/db/drizzle/0000_grey_toro.sql
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psql $DATABASE_URL -f packages/db/drizzle/0001_document_chunks.sql
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```
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> Note: on imrnes (PgBouncer `:6432`) a leaked `DATABASE_URL` shell var can
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> shadow `.env`. `@mcpedia/config` loads `.env` **last** so the repo config
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> always wins for local/dev.
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## Content
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Each Markdown file carries YAML frontmatter:
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```yaml
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---
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id: websocket-contract
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title: WebSocket Contract
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type: documentation
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tags: [typescript, websocket, rpc]
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status: published
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author: asep
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created_at: 2026-08-19
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updated_at: 2026-08-19
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---
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```
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`slug` = relative path under `content/` (e.g. `docs/websocket/contract`). The
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`body` shown in the UI is always read from the on-disk file (source of truth);
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the DB stores metadata + the search vector.
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## MCP tools
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| Tool | Purpose |
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| --------------------- | ------------------------------------------------ |
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| `search_documents` | Postgres FTS over the corpus (ranked + snippet) |
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| `semantic_search` | Embedding/cosine search over chunked content |
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| `hybrid_search` | FTS + semantic fused via RRF |
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| `get_document` | Full markdown body by slug |
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| `list_documents` | List, optionally filtered by section |
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| `get_related_documents` | Docs sharing tags with a given slug |
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Smoke test (in-memory transport, real JSON-RPC):
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```bash
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bun --cwd apps/mcp run smoke
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```
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## API (Phase 2)
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A tRPC v11 API is also exposed via Hono on **:4020** (all procedures mirror the
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MCP tools):
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```bash
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bun run api # http://localhost:4020 (GET /health, POST/GET /trpc/*)
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```
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`bun run index` now also chunks + embeds (Phase 2 indexer). Requires `EMBED_*`
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vars in `.env` (see `.env.example`).
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## Status
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**Phase 1 — MVP (DONE):** monorepo, Core, Web UI (home/doc/search), MCP server,
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Postgres FTS keyword search, content indexing.
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**Phase 2 — Semantic + API (DONE):** embeddings provider (OpenRouter via 9router),
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chunked `document_chunks`, `semanticSearch` + `hybridSearch` (RRF), tRPC/Hono API
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(`apps/api`, :4020), MCP `semantic_search`/`hybrid_search` tools, web hybrid toggle.
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> pgvector is **not installed** on the shared imrnes Postgres, so vector storage is
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> a `real[]` column with in-app cosine similarity (instant at KB scale). pgvector is
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> the Phase-4 scale-out path. See `PHASES.md`.
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See `PHASES.md` for Phase 3–4 (Redis/BullMQ, auth, revisions, scale-out).
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