MaiSaka
A human-style LLM companion designed for ongoing QQ group conversations.
- Source repo
- Mai-with-u/MaiBot
- Stars
- ★ 6.9k
- Last updated
- 7d ago
- License
- GPL-3.0
- Primary language
- Python
- FA score
- 23/100 · Major gaps
At a glance
- How it runs
- Works with
- Platform-specific
- Cost
- Free software; you pay for model usage
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- A QQ group administrator wants a conversational character for everyday group interaction instead of a command-oriented support bot.
- Not a fit if
- Teams wanting a ready-made hosted service instead of self-hosting
- Teams needing chat platforms other than QQ group chats
- Users expecting a zero-config, out-of-the-box setup
- Source review
- 23/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
MaiSaka is an interactive large-language-model agent positioned as a digital life form for QQ group chats, rather than an assistant optimized primarily for task efficiency. Its stated focus is casual conversation, appropriate timing in group discussions, and adapting to how participants express themselves. The project says it gradually builds an understanding of users’ preferences, traits, habits, and behavioral style, while learning new slang and in-group language in multi-person chats. The repository presents a WebUI and states that APIs, an event system, and a plugin system are available for extension. It is best suited to teams seeking a persistent, character-driven group-chat companion; the supplied material does not establish a general-purpose deployment path with documented model providers, APIs, or CLI operations.
MaiSaka participates in multi-person conversations in a QQ group-chat context. The project describes it as judging when to join a conversation and when to remain silent, while imitating the speech style of people in the group. Across conversations, it is intended to accumulate and use information about a user’s preferences, traits, habits, and behavioral style for more continuous interaction. The repository also shows a WebUI and states that behavior can be extended through APIs, an event system, and plugins; the supplied material does not name specific APIs, events, plugin interfaces, or runnable commands.
- A QQ group administrator wants a conversational character for everyday group interaction instead of a command-oriented support bot.
- A long-running community wants a character that can adapt to its members’ phrasing, emerging slang, and conversational atmosphere.
- A companionship-focused chat project wants interactions to build on users’ stated preferences, habits, and behavioral style over time.
- A plugin developer wants to extend group-chat behavior through the project’s stated API, event, and plugin systems.
- A team member wants to explore MaiSaka through the repository’s demonstrated WebUI.
How do you install or deploy this agent?
The only explicit runtime requirement is Python 3.12+. The material links to a deployment guide and to a Maibot OneKey launcher for Windows and macOS, but it does not provide copyable installation commands, a dependency list, configuration files, QQ connection steps, required credentials, or a first-start command. A complete verifiable installation procedure therefore cannot be derived from the supplied material.
How do you use this agent?
The material describes QQ group-chat interaction and shows a WebUI, but does not explain how to create a bot account, configure a QQ protocol, supply model credentials, start a service, or send a first message. It instructs users to read the EULA and privacy policy before use and to assess AI-generated content carefully.
What are this agent's strengths and limitations?
- Has a distinct “more lifelike, not merely better” design goal, rather than centering task completion.
- Targets multi-person QQ conversations and explicitly emphasizes timing, group atmosphere, and adaptation to participants’ language.
- States support for APIs, an event system, and a plugin system, creating an extension path.
- Shows a WebUI and links to a Windows/macOS launcher.
- The supplied material provides no copyable installation commands, configuration example, or first-run procedure.
- No supported model provider, model interface, authentication method, or cost information is identified.
- Its central use case is QQ group chat; portability to other chat platforms is not established.
- APIs, events, and plugins are claimed, but their interfaces, compatibility, and extension examples are not described in the supplied material.
How does this agent compare with similar options?
MaiSaka distinguishes itself from a conventional “helpful assistant” by prioritizing warmth, authenticity, and long-term human-like interaction over efficiency and problem solving. The README calls AstrBot an excellent LLM Agent project, but provides no verifiable feature-by-feature comparison.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| MaiSaka This agent | 23 · Major gaps | Self-hosted serviceFree + model costs | ★ 6.9k | 7d ago | Python | — |
| DeepSeek Bot | 69 · Some gaps | Desktop appFree + model costs | ★ 5.7k | 1d ago | JavaScript | — |
| Sapphire Blue AI | 53 · Major gaps | Web appFree + model costs | ★ 328 | 1d ago | Python | OpenAI API · Claude API |
| OpenBiliClaw: Local-First Cross-Platform AI Content Discovery Agent | 63 · Some gaps | Browser extensionFree + model costs | ★ 3.7k | today | Python | ChatGPT · Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows EULA and privacy policy exist, but no specific implementation of permission management, user confirmation, data flow transparency, or sensitive data handling. Dependency security not mentioned, external effects and rollback mechanisms not documented. Source attribution only via contributor list and license, but publisher unverified. Thus all trust criteria scored 0.
Self-consistency: Version numbers consistent (v1.1.4) in README and pyproject.toml, but description inconsistent (README says MaiSaka, pyproject says MaiCore). Dependency availability: dependency list complete, but no lock file or mirror instructions. Failure messages: no documentation of error handling or user prompts.
Audience and scenarios: README clearly targets QQ group chat users, scenarios clear. Capability boundaries: plugin system mentioned but limitations not detailed. Trigger precision: trigger mechanism not described. Environment fit: Windows/Mac launcher provided, but other platforms not mentioned.
Information architecture: README well-structured with documentation links. Install notes: deployment guide and launcher provided. Naming stability: project name MaiBot, but description mixes MaiSaka and MaiCore. Examples and FAQ: demo video and community groups, but no FAQ. Known limitations: not explicitly listed. License: GPL-3.0 clear. Versioning and changelog: version number but no changelog. Maintenance responsibility: contribution guide and community support.
Output usability: natural conversation style described, but no concrete output examples. Marginal value: emphasizes human-like interaction, but no comparison with other agents. Cost-benefit: no resource consumption or performance data.
Claim traceability: feature claims in README lack code or test support. Cross-source corroboration: no independent verification. Fact-inference separation: no distinction between facts and inferences.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- Publisher identity unverified, proceed with caution.
- Feature claims in README lack code or test support, verify independently.
- Dependency security not mentioned, check for vulnerabilities.
- Permission management and data flow transparency not documented, review before use.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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Release notes excerpt
细节与修复 - 优化了插件市场的加载稳定性 - 日志：默认屏蔽列表补充 httpx2、httpcore2。 - 更新：修复更新时可能出现的网络问题。 - 插件 SDK：开放全局人设列表、当前人设查询与持久化切换能力，切换保留当前编辑并热重载。 - 桌宠：开放窗口生命周期、点击、拖动和状态变化的 Hook。SDK支持注册桌宠扩展按钮、读取状态与处理点击。 WebUI [1.9.13] - 配置：桌宠移出实验性功能。 - 推理过程：修复手机端记录列表与详情面板重叠，未选择记录时隐藏详情空态。 - 人设：支持粘贴 JSON 导入及外部网页通过导入链接唤起预览、编辑与确认保存。 - 人设：支持保存多套全局备选人设、重命名、删除与手动切换，切换时保留当前编辑，配置保存后热重载生效。View on GitHub ↗ -
Release notes excerpt
细节与修复 - 修复麦麦尾巴叶子数量异常 - 注意力漂移：群聊与私聊可分别配置开关。 - Docker：恢复旧 WEBUI_HOST 环境变量兼容。 WebUI [1.9.12] - 实时监控：Planner 展示模型思考。 - 聊天：悬停聊天流可查看表达与黑话的学习/使用开关、当前回复频率、运行状态和最近消息。 - 插件设置：支持 SDK 声明二维码、动态状态和操作按钮。View on GitHub ↗ -
Release notes excerpt
主要功能 - 桌宠：支持自主 todo list 创建修改，支持发送图片，支持声明式皮肤包和自定义动画。 细节与修复 - 模板：修复模板未打包问题。 - 配置：修复升级时网络配置丢失问题。 WebUI [1.9.11] - 插件设置：支持 SDK 声明二维码、动态状态和操作按钮。View on GitHub ↗