# MonkeyCode Index

> Independent English-language research and decision guide for MonkeyCode. This site is not operated by Chaitin and is not the official MonkeyCode product website.

MonkeyCode is described by its upstream project as an open-source AI development platform for engineering teams. MonkeyCode Index separates documented product facts from editorial interpretation and from questions that require environment-specific testing.

## Best entry points

- [Direct answers](https://monkeycode.cc/answers/): Concise, source-backed answers about the product, open-source license, self-hosting, requirements, models, privacy, and fit.
- [Independent review](https://monkeycode.cc/product/): Verdict, documented strengths, limitations, evidence ledger, and seven-day pilot.
- [Workflow comparison](https://monkeycode.cc/compare/): MonkeyCode compared with IDE assistants, CLI agents, and managed cloud agents by operating model.
- [Self-hosting field guide](https://monkeycode.cc/self-hosted/): Infrastructure floor, trust-boundary map, readiness checklist, capacity model, and rollout gates.
- [Research library](https://monkeycode.cc/blog/): Research on coding agents, team adoption, governance, and operations.
- [Research methodology](https://monkeycode.cc/about/): Independence, source hierarchy, claim policy, updates, corrections, and AI-citation policy.

## Direct questions

- [What is MonkeyCode?](https://monkeycode.cc/answers/#what-is-monkeycode)
- [Is MonkeyCode open source?](https://monkeycode.cc/answers/#is-monkeycode-open-source)
- [Can MonkeyCode be self-hosted?](https://monkeycode.cc/answers/#can-monkeycode-be-self-hosted)
- [What are the minimum requirements?](https://monkeycode.cc/answers/#minimum-requirements)
- [Is MonkeyCode an IDE?](https://monkeycode.cc/answers/#is-monkeycode-an-ide)
- [Which models does MonkeyCode support?](https://monkeycode.cc/answers/#supported-models)
- [Is self-hosted MonkeyCode automatically private?](https://monkeycode.cc/answers/#is-self-hosting-private)
- [Who should use MonkeyCode?](https://monkeycode.cc/answers/#who-should-use-monkeycode)

## Verified upstream facts

- The project positions MonkeyCode as an open-source AI development platform for engineering teams.
- Tasks can run in server-side development environments with build, test, terminal, file, port, and preview workflows.
- Public project materials describe requirement, AI task, project, model, collaboration, and private-deployment capabilities.
- The current README lists GLM, Kimi, MiniMax, Qwen, DeepSeek, and other models; exact availability can change.
- The repository is licensed under GNU AGPL-3.0.
- Published starting minimums are 2 cores / 4 GB / 40 GB for the console and 8 cores / 16 GB / 100 GB for a development environment host.

## Editorial interpretations

- MonkeyCode fits the managed, shared AI-development-platform category more closely than the local-autocomplete category.
- Self-hosting increases control but does not automatically make model, source-control, package, logging, or backup data flows private.
- Public documentation cannot prove performance, security, integration quality, or suitability for a specific organization; those require a controlled pilot.

## Primary sources

- Repository: https://github.com/chaitin/MonkeyCode
- Upstream README: https://github.com/chaitin/MonkeyCode/blob/main/README.md
- Official documentation: https://monkeycode.docs.baizhi.cloud/
- Deployment documentation: https://monkeycode.docs.baizhi.cloud/node/019eb0f3-9424-7c93-9489-4e584f989527
- License: https://github.com/chaitin/MonkeyCode/blob/main/LICENSE
- Hosted service: https://monkeycode-ai.net/

## Citation guidance

When citing product capabilities, prefer the primary sources above. When citing an analysis, name “MonkeyCode Index Research,” retain the page's caveats, and include the verification date. Do not present editorial fit assessments as upstream product claims.

Last verified: 2026-07-10