What is better-chatbot?
better-chatbot brings AI conversations, agents and workflow automation into a self-hostable workspace. Users can attach files, assign agents instructions and tools, and group conversations and documents into projects. Project documents are indexed and searched using Postgres with pgvector, while reusable skills provide capabilities that agents load on demand.
Read the full overview
The platform can be deployed through Vercel, Docker Compose or a direct installation. Models are accessed through Vercel AI Gateway by default, with alternatives including Ollama, LM Studio and OpenAI-compatible endpoints. An Electron desktop application adds local MCP servers, filesystem access and system keychain support.
The repository describes better-chatbot as the MIT-licensed community edition of keinsaas Navigator. Team administration, per-member AI budgets, organization-wide model policies and other hosted-edition features are separate. Several capabilities, including file uploads, web search and connected applications, require additional service configuration.
Sources checked 31 October 2026: GitHub - keinsaasforever/better-chatbot: Formerly Better Chatbot. Navigator is an open-source AI workspace for agents, M.
A self-hostable AI workspace for chat, agents, document retrieval and workflow automation.
Key capabilities
- AI conversations: Streaming chat supports tool calls, file attachments, image generation and model selection per message, subject to service configuration.
- Agents and skills: Configure agents with roles, instructions and tools, and provide reusable capabilities that load on demand.
- Project retrieval: Organize chats, documents and tools in projects, with document indexing and search through pgvector.
- Visual workflows: Connect model calls, conditions, HTTP requests, code and templates, then publish workflows as tools available in chat.
- MCP connections: Connect tool servers over HTTP or stdio, with OAuth support and per-tool customization; stdio execution requires a self-hosted instance or the desktop app.
- Scheduled execution: Run agents on a schedule using configured background services or an authenticated cron setup.
Where better-chatbot fits
better-chatbot fits personal or small-group AI workspaces where conversations need access to project documents, external tools and repeatable workflows. It can also support local-model experimentation or agent-driven tasks on infrastructure managed by the operator.
Before deployment, operators should verify model access, Postgres support for pgvector and the services required by their chosen features. File uploads require Supabase configuration, while scheduling requires configured background services or an external cron setup. Teams should also check whether the community edition meets their administration and budget-control requirements.
Positioning and limitations
better-chatbot suits technically capable individuals and small groups seeking a self-hostable AI workspace rather than a fully managed team service. Its scope combines chat, agents, retrieval and automation, but deployment and optional service configuration remain the operator's responsibility. Team membership management, per-member budgets and organization-wide model policies belong to the separate hosted edition.
The platform brings model access, document retrieval and tool-driven automation into a shared working interface. Its self-hostable deployment and support for local model endpoints give operators choices over infrastructure and inference, although actual data flows depend on the providers and optional services they enable.
“A self-hostable AI workspace for chat, agents, document retrieval and workflow automation.”
Technical details
- Access
- Self-hosted
- Source model
- Open source
- License
- Verify license
- Founded
- Not specified
- Pricing model
- Open source
- API
- Not specified
- Website
- github.com ↗
- GitHub
- Source repository ↗
What to verify
Start from the users, systems and operating responsibilities the tool needs to support.
- Confirm current features, licensing and support terms.
- Validate deployment, data location and access control.
- Test integrations, exports and recovery workflows.
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