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

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- 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>
This commit is contained in:
“BeeRad”
2026-01-29 15:44:06 +11:00
co-authored by Claude Opus 4.5
parent 883299d070
commit a7234be5f4
1 changed files with 70 additions and 37 deletions
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README.md
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@@ -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 (Intel) | ✅ Supported |
| Linux | 🚧 Coming (requires manual sqlite-vec build) |
| Windows | 🚧 Coming (requires manual sqlite-vec build) |
| macOS (Apple Silicon) | Supported |
| macOS (Intel) | Supported |
| Linux | 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
- **BYO keys** – Your Anthropic/OpenAI keys only; nothing sent to RA-H
- **Local SQLite + sqlite-vec** – Semantic search and embeddings on your machine
- **Content extraction** – YouTube, PDF, web pipelines included
- **Workflows** – Editable JSON workflows for common tasks
- **MCP Server** – Connect Claude Code, ChatGPT, or any MCP-compatible assistant
RA-H Light exposes an MCP server that external AI assistants can use to read/write your knowledge graph.
### Claude Code Integration
Add to your Claude Code settings:
```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
services/ Agents, embeddings, ingestion, storage
tools/ Agent tools
config/ Prompts, workflows
apps/mcp-server/ MCP server for external AI assistants
docs/ Local docs (mirrors ra-h.app/docs)
components/ UI components
services/ Database, embeddings, workflows
tools/ Available tools for workflows
apps/mcp-server/ MCP server (stdio + HTTP)
docs/ Local documentation
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)
Local reference:
- [docs/0_overview.md](docs/0_overview.md) – Overview
- [docs/1_architecture.md](docs/1_architecture.md) – Architecture
- [docs/0_overview.md](docs/0_overview.md) – System overview
- [docs/2_schema.md](docs/2_schema.md) – Database schema
- [docs/8_mcp.md](docs/8_mcp.md) – MCP server setup
- [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md) – Common issues
- [docs/8_mcp.md](docs/8_mcp.md) – MCP server details
## 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):
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.
Without sqlite-vec: UI, node CRUD, and basic search still work. Vector/semantic search requires it.
## Contributing