head to head · open source

Agenta vs Compartment

Agenta has 4,766 GitHub stars, 674 forks, 309 open issues and last shipped today. Compartment has 581 stars, 5 forks, 1 open issues and last shipped 3 days ago. Agenta leads on adoption by 720% (4,766 vs 581 stars). Agenta is written in TypeScript under a custom or non-standard licence; Compartment is written in Python under Apache-2.0. Agenta has attracted 14% as many forks as stars, Compartment 1%. Agenta was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai-agents), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Agenta ★ 4.8K Compartment ★ 581 category AI & Machine Learning

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Side by side

Agenta Compartment
GitHub stars ★ 4.8K ★ 581
License Custom / other Apache-2.0
Written in TypeScript Python
Last push 2026-09-20 2026-09-17
Forks ⑂ 674 ⑂ 5
Self-hosting Yes Yes
Data ownership Your server Your server

pick Agenta if

  • You weight community size — 4.8K stars and counting
  • You want the Custom / other license terms
  • Your stack matches TypeScript
  • You value the larger contributor base for long-term maintenance

full Agenta profile →

pick Compartment if

  • You want the Compartment feature set and don't need the biggest community
  • You prefer the Apache-2.0 license terms
  • Your stack matches Python
  • You evaluated both and Compartment fits your workflow better

full Compartment profile →

About Agenta

Agenta is an open source workspace where a team builds, runs, and improves AI agents by chatting with them, intended for individuals and teams that want agent automation without moving every task onto metered API billing.

read the full Agenta overview →

About Compartment

Compartment is an Apache 2.0 Python MCP server that gives AI agents encrypted, fully offline long term memory in a single vault on the user's own computer, built for people running Claude Code, Claude Desktop, Cursor, Codex, Hermes Agent, OpenClaw or any other MCP client who want persistent memory with no account, no API key, no network and no telemetry.

read the full Compartment overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

Related comparisons

openclaw vs ollama ollama vs llama-cpp ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

Agenta vs Ollama Agenta vs llama.cpp Agenta vs vllm Agenta vs GPT4All Agenta vs llama_index Agenta vs LocalAI Agenta vs faiss Agenta vs PageIndex Agenta vs Langfuse Agenta vs cognee Agenta vs taipy Agenta vs dagster

Frequently asked questions

Is Agenta or Compartment more popular?

Agenta has 4,766 GitHub stars and Compartment has 581. Agenta has the larger community by that measure.

Are Agenta and Compartment free?

Both are open source. Agenta has no licence declared in this registry, and Compartment is licensed under Apache-2.0. Both are free to self-host.

What is the difference between Agenta and Compartment?

Agenta is written in TypeScript and Compartment in Python. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Agenta or Compartment?

Choose Agenta if you want the larger community (4,766 stars) or its Custom / other licence terms. Choose Compartment if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.