head to head · open source
ragflow vs Multica
ragflow has 90,889 GitHub stars, 10,759 forks, 1,525 open issues and last shipped yesterday. Multica has 50,299 stars, 6,507 forks, 1,538 open issues and last shipped yesterday. ragflow leads on adoption by 81% (90,889 vs 50,299 stars). ragflow is written in Go under Apache-2.0; Multica is written in Go under a custom or non-standard licence. ragflow has attracted 12% as many forks as stars, Multica 13%. ragflow was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| ragflow | Multica | |
|---|---|---|
| GitHub stars | ★ 91K | ★ 50K |
| License | Apache-2.0 | Custom / other |
| Written in | Go | Go |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 11K | ⑂ 6.5K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick ragflow if
- You weight community size — 91K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick Multica if
- You want the Multica feature set and don't need the biggest community
- You prefer the Custom / other license terms
- Your stack matches Go
- You evaluated both and Multica fits your workflow better
About ragflow
RAGFlow is an open source Retrieval Augmented Generation engine that fuses RAG with agent capabilities into a context layer for large language models, built for developers and teams that need to turn complex, unstructured documents into production AI systems.
read the full ragflow overview →
About Multica
Multica is an open source project management platform designed for teams combining human developers and AI coding agents. It operates in the AI development ecosystem, providing a unified workspace where agents function as first class collaborators alongside people. The platform solves the problem of fragmented agent workflows: when using multiple AI tools like Claude Code, Codex, or Cursor in separate terminal sessions, context is lost between runs, coordination becomes manual, and oversight is difficult. Multica centralizes agent execution, assignment, and review into a single system where work flows from issue …
read the full Multica overview →
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Frequently asked questions
Is ragflow or Multica more popular?
ragflow has 90,889 GitHub stars and Multica has 50,299. ragflow has the larger community by that measure.
Are ragflow and Multica free?
Both are open source. ragflow is licensed under Apache-2.0, and Multica has no licence declared in this registry. Both are free to self-host.
What is the difference between ragflow and Multica?
ragflow is written in Go and Multica in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, ragflow or Multica?
Choose ragflow if you want the larger community (90,889 stars) or its Apache-2.0 licence terms. Choose Multica if its feature set, stack or Custom / other licence fits better. Both are self-hostable.