AI Skill Hub 推荐使用:Anchored AI编码助手 是一款优质的AI工具。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AI工具解决方案,这是一个值得深入了解的选择。
为AI编码代理提供持久化跨工具内存管理的开源工作流框架。单一二进制文件,零依赖设计,支持多工具协作。适合开发者构建智能代码生成和自动化工具链。
Anchored AI编码助手 是一款基于 Go 开发的开源工具,专注于 AI工作流、代码代理、内存管理 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
为AI编码代理提供持久化跨工具内存管理的开源工作流框架。单一二进制文件,零依赖设计,支持多工具协作。适合开发者构建智能代码生成和自动化工具链。
Anchored AI编码助手 是一款基于 Go 开发的开源工具,专注于 AI工作流、代码代理、内存管理 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:go install(推荐) go install github.com/jholhewres/anchored@latest # 方式二:从源码编译 git clone https://github.com/jholhewres/anchored cd anchored go build -o anchored . # 方式三:下载预编译二进制 # 访问 Releases 页面下载对应平台二进制文件 # https://github.com/jholhewres/anchored/releases
# 查看帮助 anchored --help # 基本运行 anchored [options] <input> # 详细使用说明请查阅文档 # https://github.com/jholhewres/anchored
# anchored 配置说明 # 查看配置选项 anchored --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 ANCHORED_CONFIG="/path/to/config.yml"
Persistent cross-tool memory for AI coding agents. Local-first, single binary, zero dependencies.
Anchored gives Claude Code, Cursor, OpenCode, Gemini CLI, Codex, VS Code Copilot, and other MCP-compatible tools one shared memory database on your machine.
anchored is both the CLI and MCP server.For team-shared project memory, the optional self-hosted/server side lives in anchored_oss. Local Anchored remains the source of truth and the hot retrieval path.
anchored_context returns identity, project stats, recent durable knowledge, and recent important session events under a tight budget..mdc, and DevClaw.From GitHub Releases:
curl -fsSL https://raw.githubusercontent.com/jholhewres/anchored/main/install/install.sh | bash
From source:
git clone https://github.com/jholhewres/anchored.git
cd anchored
make build
sudo cp bin/anchored /usr/local/bin/
First run creates ~/.anchored/ and downloads the local embedding model when needed (~470 MB).
curation:
enabled: true
interval_minutes: 15
threshold: 0.55
max_updates_per_run: 50
sanitizer:
enabled: true
patterns:
- 'ACME_[A-Z0-9]{32}'
context_optimizer:
enabled: false
Show or edit config:
anchored config show
anchored config set curation.enabled false
anchored config wizard
anchored Start MCP server over STDIO
anchored serve Start MCP server over STDIO
anchored init [--tool] Register Anchored with supported tools
anchored doctor [--cwd] Diagnose binary, model, DB, and MCP registration
anchored stats Show memory counts and import status
anchored save <content> Save a memory
anchored search <query> Search memories
anchored list List memories
anchored inspect <id> Show full JSON metadata
anchored update <id> Revise a memory in place
anchored forget <id> Soft-delete a memory; --hard for permanent delete
anchored export Export memories as JSON/JSONL
anchored curation status Show background curation worker state
anchored curation enable Enable serve-time curation worker
anchored curation disable Disable serve-time curation worker
anchored curation score Score and optionally mark low-signal memories
anchored curation clean Soft-delete or hard-delete low-signal memories
anchored curation restore Restore a DB backup made before curation cleanup
anchored dream Analyze duplicate/contradictory memories
anchored dream --apply <id> Apply one proposed dream action
anchored retention sweep Archive expired operational/episodic memories
anchored bootstrap [--cwd] Extract project seed memories from README/docs/rules/tree
anchored handoff [--scope] Save a short session handoff with TTL
anchored precompact Save a pre-compaction recovery snapshot
anchored hook <subcommand> Run session continuity hooks
anchored remote status Show remote sync configuration
anchored remote configure Configure a remote server
anchored remote link|unlink Link/unlink remote project IDs
anchored remote preview Offline preview of syncable/blocked memories
anchored remote sync Push syncable memories and KG triples
anchored purge Wipe memories; --hard resets DB with backup
Import sources: claude-code, devclaw, opencode, cursor, all.
The plugin is the easiest path because it installs MCP registration, slash commands, hooks, and the auto-trigger skill together:
/plugin marketplace add jholhewres/anchored
/plugin install anchored@anchored
Restart Claude Code after installation. Available slash commands include /anchored:context, /anchored:search, /anchored:save, /anchored:stats, /anchored:doctor, and /anchored:purge.
Running context-mode too? Anchored now ships its own PreToolUse routing — it steers Read/Grep/Glob/Bash/WebFetch and subagents toward memory and the sandbox tools, the same mechanism context-mode uses. Running both plugins means two routing blocks competing for the model's attention, and context-mode's redirects can shadow Anchored's. Uninstall context-mode for the cleanest behavior — Anchored covers both the memory and the context-window story on its own.
Anchored has two maintenance paths because they solve different problems:
| Path | Default | What it does | Safety model |
|---|---|---|---|
curation | On | Scores recent memories in small batches, sets importance, and marks low_signal. | Non-destructive. No content rewrites or deletes. |
dream | Manual | Finds duplicates, merge/supersede opportunities, and contradictions. | Proposed actions; destructive operations require explicit apply/review. |
The curation worker starts with anchored serve. By default it runs every 15 minutes, processes newest candidates first, and updates at most 50 memories per pass. Tune or disable it with:
anchored curation status
anchored curation disable
anchored curation enable
anchored config set curation.interval_minutes 5
anchored config set curation.max_updates_per_run 25
anchored config set curation.threshold 0.55
Use anchored curation clean --dry-run when you want to remove low-signal memories. Cleanup is never automatic.
创新的AI工作流框架,零依赖设计降低部署成本。但项目成熟度有限,社区规模小,适合早期探索者。
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。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,Anchored AI编码助手 是一款质量良好的AI工具,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 | anchored |
| 原始描述 | 开源AI工作流:Persistent cross-tool memory for AI coding agents. Single binary. Zero dependenc。⭐6 · Go |
| Topics | AI工作流代码代理内存管理Go语言零依赖 |
| GitHub | https://github.com/jholhewres/anchored |
| License | MIT |
| 语言 | Go |
收录时间:2026-06-04 · 更新时间:2026-06-11 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。