Your Private AI Workspace

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What is ClaraVerse?

ClaraVerse is a private AI workspace that combines chat, visual workflows, long-running tasks, and Telegram integration in one app. Assign Clara research, coding, or automation tasks and track everything on a board. Use OpenAI, Claude, Gemini, or local models like Ollama — with browser-local storage that keeps your conversations private.

If you have Ollama or LM Studio running on your machine, ClaraVerse detects them automatically and imports all your models — zero configuration.

Quick Start

One-line install (Linux / macOS)

curl -fsSL https://raw.githubusercontent.com/claraverse-space/ClaraVerse/main/cli/install.sh | bash && claraverse init

Docker Compose

git clone https://github.com/claraverse-space/ClaraVerse.git
cd ClaraVerse
docker compose -f docker-compose.production.yml up -d

Open http://localhost:3000 — register your account (first user becomes admin) and start chatting.

Have Ollama running? ClaraVerse auto-detects it and imports all your models. No setup needed. Make sure Ollama is listening on 0.0.0.0 (set OLLAMA_HOST=0.0.0.0 in your Ollama config).

<details> <summary>Docker run (single command)</summary>

docker run -d \
  --name claraverse \
  -p 3000:3000 \
  -v claraverse-data:/app/data \
  -v claraverse-uploads:/app/uploads \
  --add-host=host.docker.internal:host-gateway \
  ghcr.io/claraverse-space/claraverse:latest

This runs ClaraVerse with a single container. For the full stack with MySQL, MongoDB, Redis, and SearXNG, use the Docker Compose setup above.

</details> <details> <summary>Advanced configuration</summary>

Prerequisites

Docker & Docker Compose v2+
4 GB RAM minimum (8 GB recommended)
Ollama, LM Studio, or any OpenAI-compatible API

Environment variables

Override defaults by creating a .env file next to docker-compose.production.yml:

# Port (default 3000)
CLARAVERSE_PORT=8080

# Point to a custom Ollama or LM Studio URL
OLLAMA_BASE_URL=http://host.docker.internal:11434
LMSTUDIO_BASE_URL=http://host.docker.internal:1234

Local AI auto-detection

ClaraVerse automatically discovers local AI providers running on your host machine:

| Provider | Default URL | What happens | | ------------------- | ------------------------------------- | ------------------------------------------------- | | Ollama | http://host.docker.internal:11434 | Models imported, provider created, visibility set | | LM Studio | http://host.docker.internal:1234 | Models imported via OpenAI-compatible API |

The discovery runs every 2 minutes. When a provider goes offline, it's automatically disabled. When it comes back, models are re-imported.

Ollama setup tip: Ollama defaults to 127.0.0.1 which Docker containers can't reach. Set OLLAMA_HOST=0.0.0.0:

# If using systemd:
sudo systemctl edit ollama
# Add under [Service]:
# Environment="OLLAMA_HOST=0.0.0.0"
sudo systemctl restart ollama

Troubleshooting

# View logs
docker compose -f docker-compose.production.yml logs -f claraverse

# Restart
docker compose -f docker-compose.production.yml restart

# Fresh start (removes all data)
docker compose -f docker-compose.production.yml down -v && docker compose -f docker-compose.production.yml up -d

</details>

Core Capabilities

Nexus — Your AI Command Center

Assign Clara long-running tasks like research, coding, or analysis. Track everything on a Kanban board — you always know what she's working on and why. No black box.

Skills in Chat

Clara uses skills mid-conversation — context-aware tools that activate when needed. Search the web, generate images, analyze data, all without leaving the chat.

Channels — Telegram Integration

Talk to Clara from Telegram when you're away from the app. Set up routines that run on a schedule and report back to your phone.

150+ Integrations & Tools Out of the Box

Slack, GitHub, Jira, Google Sheets, Notion, Discord, Telegram, HubSpot, and many more — built in, no MCP required. All integrations are shared across Chat, Workflows, Nexus, and Routines. Connect once, use everywhere.

Interactive Artifacts

Have all your creations in one place — images, charts, games, apps and more.

AI Docs

Built-in tools for PPT, PDF, CSV and much more.

Interactive Chat UI (Human in the Loop)

The AI asks you visual questions when it needs your input.

Workflows — Visual Automation

Drag-and-drop workflow builder with parallel execution, scheduling, and 200+ integrations. Describe what you need and let the LLM build the automation for you.

Schedule, API and Automate

Use workflows with your web apps, schedule daily messages, automate repetitive tasks.

Key Features

| Feature | Description | | --------------------------------- | ---------------------------------------------------------------------------- | | Nexus | Assign long-running tasks, track progress on a Kanban board | | Skills | Context-aware tools that activate mid-conversation when needed | | Channels | Telegram integration — talk to Clara from your phone | | Routines | Scheduled task sequences that report back via Telegram | | Workflows | Drag-and-drop builder with parallel execution, scheduling, 200+ integrations | | 150+ Integrations | Slack, GitHub, Jira, Notion, and more — shared across Chat, Workflows, Nexus, and Routines | | Devices | Connect all your machines — Clara reaches MCP on any of them remotely | | Clara Companion | Bridge local MCP servers to ClaraVerse over WebSocket from any machine | | Browser-Local Storage | Conversations stay in IndexedDB — zero-knowledge architecture | | Local AI Auto-Detection | Ollama and LM Studio discovered and imported automatically | | Multi-Provider | OpenAI, Anthropic, Google, Ollama, any OpenAI-compatible endpoint | | MCP Bridge | Native Model Context Protocol support for seamless tool connections | | Interactive Prompts | AI asks clarifying questions mid-conversation with typed forms | | Memory System | Clara remembers context across conversations, auto-archives old memories | | BYOK | Bring your own API keys or use free local models |

Clara Companion (MCP Bridge)

Connect your local tools and filesystem to ClaraVerse via the Clara Companion CLI. It bridges local MCP servers to your ClaraVerse instance over WebSocket.

# Install via the claraverse CLI
claraverse companion

# Login (choose default localhost:3000 or enter your server URL)
clara_companion login

# Start the bridge
clara_companion

Or install manually from GitHub Releases.

Try It Out

| Option | Description | | ------------------------------------------------------------------------ | -------------------------------------------------------------------- | | Cloud | Free hosted version — no setup required | | Self-Hosted | Docker deployment (this repo) — full

ClaraVerse

Install / Use

README