feat(rah-light): update README for lite version

- Rename to RA-H Light
- Describe as knowledge management backend for AI agents
- Add MCP integration section with Claude Code setup
- List all 11 available MCP tools
- Remove references to chat agents, voice, 3-panel interface
- Keep essential sections: quick start, project layout, commands, docs

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

README.md

@@ -1,17 +1,26 @@
-# RA-H Open Source
+# RA-H Light
 
-A local-first AI research workspace. Full 3-panel interface, vector search, content ingestion, workflows, and conversation agents. BYO API keys, no cloud dependencies.
+A lightweight local knowledge graph UI with MCP server. Connect your AI coding agents to a personal knowledge base. BYO API keys, no cloud dependencies.
 
-**Full Documentation:** [ra-h.app/docs](https://ra-h.app/docs)
+## What is RA-H Light?
+
+RA-H Light is a stripped-down version of RA-H focused on being a **knowledge management backend for AI agents**. It provides:
+
+- **2-panel UI** – Nodes list + focus panel for viewing/editing knowledge
+- **SQLite + sqlite-vec** – Local vector database with semantic search
+- **MCP Server** – Connect Claude Code, Cursor, or any MCP-compatible AI assistant
+- **Workflows** – Editable JSON workflows for multi-step operations
+
+**What's removed:** Built-in chat agents, voice features, delegation system. RA-H Light is designed for technical users who want to bring their own AI agents via MCP.
 
 ## Platform Support
 
 | Platform | Status |
 |----------|--------|
-| macOS (Apple Silicon) | ✅ Supported |
+| macOS (Apple Silicon) | Supported |
-| macOS (Intel) | ✅ Supported |
+| macOS (Intel) | Supported |
-| Linux | 🚧 Coming (requires manual sqlite-vec build) |
+| Linux | Requires manual sqlite-vec build |
-| Windows | 🚧 Coming (requires manual sqlite-vec build) |
+| Windows | Requires manual sqlite-vec build |
 
 ## Quick Start
 
@@ -24,30 +33,65 @@ scripts/dev/bootstrap-local.sh
 npm run dev
 ```
 
-Open http://localhost:3000 → **Settings → API Keys** → add your OpenAI/Anthropic keys.
+Open http://localhost:3000 → **Settings → API Keys** → add your OpenAI key (for embeddings).
 
-## Features
+## Connecting AI Agents via MCP
 
-- **3-Panel interface** – Nodes, focus, and chat in one view
+RA-H Light exposes an MCP server that external AI assistants can use to read/write your knowledge graph.
-- **BYO keys** – Your Anthropic/OpenAI keys only; nothing sent to RA-H
+
-- **Local SQLite + sqlite-vec** – Semantic search and embeddings on your machine
+### Claude Code Integration
-- **Content extraction** – YouTube, PDF, web pipelines included
+
-- **Workflows** – Editable JSON workflows for common tasks
+Add to your Claude Code settings:
-- **MCP Server** – Connect Claude Code, ChatGPT, or any MCP-compatible assistant
+
+```json
+{
+  "mcpServers": {
+    "rah": {
+      "command": "node",
+      "args": ["/path/to/ra-h_os/apps/mcp-server/stdio-server.js"]
+    }
+  }
+}
+```
+
+### Available MCP Tools
+
+| Tool | Description |
+|------|-------------|
+| `rah_add_node` | Create a new knowledge node |
+| `rah_search_nodes` | Search nodes by text |
+| `rah_update_node` | Update an existing node |
+| `rah_get_nodes` | Get nodes by ID |
+| `rah_create_edge` | Connect two nodes |
+| `rah_query_edges` | Find connections |
+| `rah_update_edge` | Update a connection |
+| `rah_create_dimension` | Create a tag/category |
+| `rah_update_dimension` | Update a dimension |
+| `rah_delete_dimension` | Delete a dimension |
+| `rah_search_embeddings` | Semantic vector search |
+
+### HTTP MCP Server
+
+For non-stdio clients, start the HTTP server:
+
+```bash
+node apps/mcp-server/server.js
+```
+
+Listens on `http://127.0.0.1:44145/mcp` by default.
 
 ## Project Layout
 
 ```
 app/                 Next.js App Router
 src/
-  components/        UI
+  components/        UI components
-  services/          Agents, embeddings, ingestion, storage
+  services/          Database, embeddings, workflows
-  tools/             Agent tools
+  tools/             Available tools for workflows
-  config/            Prompts, workflows
+apps/mcp-server/     MCP server (stdio + HTTP)
-apps/mcp-server/     MCP server for external AI assistants
+docs/                Local documentation
-docs/                Local docs (mirrors ra-h.app/docs)
 scripts/             Dev helpers
-vendor/              Pre-built binaries (sqlite-vec, yt-dlp)
+vendor/              Pre-built binaries (sqlite-vec)
 ```
 
 ## Commands
@@ -62,31 +106,20 @@ vendor/              Pre-built binaries (sqlite-vec, yt-dlp)
 
 ## Documentation
 
-**Primary:** [ra-h.app/docs](https://ra-h.app/docs)
+- [docs/0_overview.md](docs/0_overview.md) – System overview
-
-Local reference:
-- [docs/0_overview.md](docs/0_overview.md) – Overview
-- [docs/1_architecture.md](docs/1_architecture.md) – Architecture
 - [docs/2_schema.md](docs/2_schema.md) – Database schema
-- [docs/8_mcp.md](docs/8_mcp.md) – MCP server setup
+- [docs/8_mcp.md](docs/8_mcp.md) – MCP server details
-- [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md) – Common issues
 
 ## Linux/Windows Setup
 
-The bundled `sqlite-vec` and `yt-dlp` binaries are macOS-only. For other platforms:
+The bundled `sqlite-vec` binary is macOS-only. For other platforms:
 
-**sqlite-vec** (required for vector search):
 1. Clone https://github.com/asg017/sqlite-vec
 2. Build for your platform
 3. Place at `vendor/sqlite-extensions/vec0.so` (Linux) or `vec0.dll` (Windows)
 4. Set `SQLITE_VEC_EXTENSION_PATH` in `.env.local`
 
-**yt-dlp** (required for YouTube extraction):
+Without sqlite-vec: UI, node CRUD, and basic search still work. Vector/semantic search requires it.
-1. Download from https://github.com/yt-dlp/yt-dlp/releases
-2. Place at `vendor/bin/yt-dlp`
-3. `chmod +x vendor/bin/yt-dlp` (Linux)
-
-Without sqlite-vec: UI, node CRUD, basic search, chat, and content extraction still work. Vector/semantic search requires it.
 
 ## Contributing