MaxKB vs airweave
Knowledge-based AI agents and shared retrieval compared
MaxKB provides a platform for building AI agents that use organizational knowledge, workflows, and tools. airweave focuses on syncing and searching data across connected sources, providing reusable retrieval infrastructure for agents and RAG systems.
MaxKB: Build and Run Enterprise AI Agents
MaxKB is a self-hostable platform for building AI agents that use company knowledge, workflows, and external tools. It suits teams that want to add model-backed question answering to internal or customer-facing systems.
airweave: Retrieve Shared Context for AI Agents
Airweave syncs data from connected apps, databases, and documents into a unified search layer for AI agents and RAG systems. It suits teams that want reusable retrieval infrastructure instead of building separate ingestion pipelines for each agent.
| MaxKB | airweave | |
|---|---|---|
| Language | Python | Python |
| License | GPL-3.0 | MIT |
| Stars | 22.9k | 6.6k |
| Forks | 3.2k | 823 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- MaxKB combines knowledge ingestion, retrieval, agent workflows, and tool use; airweave centers on connecting, syncing, and searching data sources.
- MaxKB can handle text, image, audio, and video input and output, while airweave emphasizes unified search through SDKs, a REST API, MCP, and agent-framework integrations.
- MaxKB is written in Python and uses Vue.js, Django, LangChain, PostgreSQL, and pgvector; airweave is written in Python and documents PostgreSQL, Vespa, Temporal, and Redis.
- MaxKB is licensed under GPL-3.0, while airweave is licensed under MIT.
- Both support self-hosting, but MaxKB documents a container and persistent-data setup, while airweave documents Docker Compose and lists Kubernetes for production deployment.
- MaxKB is not marked archived and has 22.9k stars; airweave is marked archived and has 6.6k stars.
Choose MaxKB if you…
- need to build knowledge-based agents with workflows and tool use.
- want to integrate question answering into business systems and connect public or private models.
- need document-grounded assistants that can handle text, image, audio, or video input and output.
Choose airweave if you…
- want a shared retrieval layer across connected apps, databases, and documents.
- need SDKs, a REST API, MCP, or agent-framework integrations to access indexed data.
- want CLI tools for managing sources, searching collections, and triggering syncs.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.