AI Skill Hub 推荐使用:Muninn AI工作流引擎 是一款优质的Agent工作流。AI 综合评分 7.2 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
隐私优先的递归上下文网关,为AI编码代理设计。支持安全的代码上下文管理和工作流编排,适合构建隐私保护的AI编程助手和自动化代理系统。
Muninn AI工作流引擎 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
隐私优先的递归上下文网关,为AI编码代理设计。支持安全的代码上下文管理和工作流编排,适合构建隐私保护的AI编程助手和自动化代理系统。
Muninn AI工作流引擎 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:cargo install(推荐) cargo install muninn # 方式二:从源码编译 git clone https://github.com/colliery-io/muninn cd muninn cargo build --release # 二进制在 ./target/release/muninn
# 查看帮助 muninn --help # 基本运行 muninn [options] <input> # 详细使用说明请查阅文档 # https://github.com/colliery-io/muninn
# muninn 配置说明 # 查看配置选项 muninn --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export MUNINN_CONFIG="/path/to/config.yml"
<p align="center"> <img src="image.png" alt="Muninn" width="400"> </p>
<p align="center"> <strong>Privacy-first recursive context gateway for agentic coding</strong> </p>
<p align="center"> <a href="#installation">Installation</a> • <a href="#using-muninn-with-claude-code">Quick Start</a> • <a href="#configuration">Configuration</a> • <a href="#tested-backends-and-known-flakiness">Tested Backends</a> • <a href="#how-it-works">How It Works</a> </p>
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Named for Odin's raven of Memory — Muninn enables AI coding agents to understand large codebases without sacrificing privacy, burning through your token budget, or suffering from session amnesia.
Built for developers on Claude Pro or Max plans who want to stretch their token budgets further. Muninn offloads expensive codebase exploration to fast, cheap models so Claude only sees what matters.
```bash
From inside Claude Code, add the muninn marketplace once, then install the plugin:
/plugin marketplace add colliery-io/muninn
/plugin install muninn-cc
Claude Code clones the repo to its plugin cache and loads the hook from there. To pull plugin updates later, run /plugin marketplace update muninn inside CC.
Hacking on the plugin source? If you're developing against a local checkout rather than the GitHub copy, load it directly with --plugin-dir at session start:
claude --plugin-dir /absolute/path/to/muninn/plugins/muninn-cc
/reload-plugins picks up plugin file edits without a full restart.
The plugin's UserPromptSubmit hook fires once per user turn: a cheap router model decides whether the prompt needs exploration; if it does, muninn drives its recursive exploration loop on the configured local/cheap backend and injects the result as additionalContext, framed as the answer for Claude to deliver. Failure mode is always silent passthrough — the hook never blocks the user's turn. See plugins/muninn-cc/README.md.
[ollama] api_key = "..." ```
You can also export OLLAMA_API_KEY in your shell — but be aware: when Claude Code launches muninn's hook + MCP subprocesses, they may not inherit your interactive shell's environment (especially if you started CC from a desktop launcher rather than a terminal). Putting the key in .muninn/config.toml is the most reliable path. The same applies to GROQ_API_KEY / ANTHROPIC_API_KEY.
For Groq, Anthropic direct, or a local Ollama daemon, see Configuration.
That's the binary side done. Now wire it into your agent.
query_graph returns empty results against a fresh .muninn/graph.db. To populate it for this repo:
muninn index
The search_code MCP tool works without the graph (it walks the filesystem directly). Indexing only unlocks query_graph.
Muninn stores data in .muninn/ within your project:
.muninn/
├── config.toml # tiered config (provider/model)
├── graph.db # code graph
├── docs.db # indexed library docs
└── sessions/ # per-session logs and traces
[default] is the baseline. [router] and [rlm] each accept optional provider / model overrides; unset fields inherit from [default]. The minimal config is empty — defaults handle the rest.
Worked example — tier a cheap router with a stronger but still cheap RLM, both within the same provider:
```toml [default] provider = "ollama" model = "gemma4:31b"
[router]
创新的隐私优先架构,Rust性能优异,递归上下文管理设计独特。但生态成熟度有限,适合专业开发者和隐私敏感场景。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
总体来看,Muninn AI工作流引擎 是一款质量良好的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | muninn |
| 原始描述 | 开源AI工作流: Privacy-first recursive context gateway for AI coding agents。⭐12 · Rust |
| Topics | AI代理工作流编排隐私保护编码助手Rust上下文管理 |
| GitHub | https://github.com/colliery-io/muninn |
| License | Apache-2.0 |
| 语言 | Rust |
收录时间:2026-05-22 · 更新时间:2026-05-30 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端