Your Private AI Workspace

Built by the community, for the community. Private AI that respects your freedom.

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What is ClaraVerse?

ClaraVerse is a private AI workspace built around three things most AI chat UIs treat as an afterthought: agents that work as an actual team, memory that behaves like a real memory system instead of a flat list of notes, and a license that does not start charging you once people notice your project.

Chat, Crew (multi-agent teams with human review), a visual workflow builder, and Telegram integration all live in one app, on your own infrastructure. Use OpenAI, Claude, Gemini, or local models like Ollama and llama.cpp. Chats are stored locally on your device by default, with optional encrypted sync if you want them on more than one machine.

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).

Want it in your terminal too?

claraverse agent install   # builds Clara Agent, puts `claracli` on your PATH
claracli                   # then run /login claraverse to connect it

See Clara Agent below.

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

# 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

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

# 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

Core Capabilities

Crew: Agent Teams With Human Review

Give a project a brief, hire a team of agents, and work the card pipeline. Every card comes back for your review before it ships, so you always know what's being worked on and why. No black box.

Memory: Layered, Encrypted, and Actually Used

Clara remembers you across conversations without being told twice. Facts are extracted automatically in the background, pulled back in only when relevant to the current conversation, and every entry is visible and editable in Settings. Nothing is stored that you can't see or delete.

• Pinned tier: mark a fact as always-inject (allergies, hard constraints, how you want to be addressed). Pinned memories skip relevance scoring and never decay.
• Recall tier: everything else, retrieved by embedding similarity against the current conversation so only what's relevant gets injected.
• Decay: unused memories lose relevance over time and archive themselves automatically.
• Model-driven: Clara calls search_memory and add_memory mid-conversation, the same way it calls any other tool.
• Encrypted at rest: AES-256-GCM with a key derived per user via HKDF. Not even a ClaraVerse admin can read your memories.

Clara Agent: The Same Assistant, In Your Terminal

Clara Agent is a coding agent that runs in your terminal and ships in this repo. It reads, writes, and edits files and runs commands on your machine, using the same model and account as the web app.

claraverse agent install   # builds it and puts `claracli` on your PATH
claracli                   # start it in any project directory

Then run /login claraverse inside the agent. You get a short code to confirm in the browser, and it picks up whichever model your account is configured with. The machine then shows up under Settings → Devices, where you can revoke it at any time.

It talks directly to your configured model provider, so it keeps working even when the ClaraVerse server is down, and it makes no network calls to anything except your own instance and your own model provider.

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, Crew, 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.

ClaraVerse vs Open WebUI

Open WebUI is the biggest self-hosted AI chat UI, and a good one. It has a bigger community, more vector database integrations, and a deeper document extraction pipeline than we do. We're not pretending otherwise. But it is a chat UI with tools bolted on. ClaraVerse is built differently, and it shows in three places.

If you need enterprise SSO, SCIM provisioning, and a large plugin marketplace today, Open WebUI is more mature there. If you want agents that act like a team, memory that behaves like an actual memory system, and a license that doesn't ask you to pay once you succeed, that's what ClaraVerse is for.

Key Features

Try It Out

Tech Stack

Development Setup

For contributors working on the codebase:

# Prerequisites: Go 1.24+, Node.js 20+, Docker

# Clone the repo
git clone https://github.com/claraverse-space/ClaraVerse.git
cd ClaraVerse

# Start backing services (MySQL, MongoDB, Redis, SearXNG)
docker compose -f docker-compose.dev.yml up -d

# Backend
cd backend
cp .env.example .env
go run cmd/server/main.go

# Frontend (separate terminal)
cd frontend
cp .env.example .env
npm install
npm run dev

Frontend runs at http://localhost:5173, backend at http://localhost:3001.

See CONTRIBUTING.md for coding standards and PR guidelines.

Documentation

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make changes and test
4. Run cd frontend && npm run lint && npm run type-check
5. Commit and open a Pull Request

Areas we need help:

• Bug fixes (open issues)
• New tool integrations and model providers
• Documentation improvements
• Translations

See CONTRIBUTING.md for the full guide.

Community

• Discord: Chat and support
• Twitter/X: Updates
• GitHub Issues: Bug reports
• GitHub Discussions: Feature requests

License

AGPL-3.0: free to use, modify, and host commercially. Modifications must be open-sourced. No branding clause, no user cap, no enterprise tier required to remove our name from your product. See LICENSE for details.