
Repomemory
io.github.DanielGuru由 GitHub 账号 DanielGuru 发布v1.3.0更新于 Oct 24, 2026
Persistent memory for AI coding agents. Hybrid search, auto-session capture, context routing.
发布方自己的服务:RepoMemory
概览
为 AI 编程代理提供持久、可搜索的项目记忆,通过工具对仓库的 .context 知识库进行搜索、读取、写入和删除。
- 可以做什么
- 搜索与定位:在仓库与全局上下文中做关键词加语义的混合搜索,并一次性返回索引、偏好和近期会话的定位信息。
- 读取与浏览:读取完整条目,优先仓库、回退全局,并按来源标签列出条目。
- 写入与维护:按作用域路由记录事实、决策、回归问题和偏好,并删除过时知识。
- 风险评估:针对整个代码库或指定文件报告热点、隐藏耦合和巴士因子。
- 会话与历史:关闭时自动保存会话摘要,并可将 git 历史同步为变更日志。
- 适用场景
- 适合在同一个代码库上跨多次 AI 会话工作时使用,让代理不再重复摸索架构、重复争论已定决策或重新引入已修复的缺陷。也适合希望共享可搜索项目知识、而非依赖静态说明文件的团队。
- 运行要求
- 通过 npx 在本地运行(需要 Node.js)。安装命令会向 Claude Code、Cursor、Copilot、Windsurf、Cline、Aider、Continue 等工具写入 MCP 配置和规则。AI 分析需要模型提供商密钥,如 ANTHROPIC_API_KEY、OPENAI_API_KEY、GEMINI_API_KEY 或 GROK_API_KEY;Cursor 方式可不用外部密钥。可选嵌入使用 Gemini 或 OpenAI 密钥。
安装
在 SourceWeft 中
- 打开 控制台中的 Repomemory,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
repomemory
Your codebase never forgets.
AI agents lose context every session. repomemory fixes that — one command creates a persistent, searchable knowledge base that any AI tool can read, search, and write to.
The Problem
Every time you open a project with Claude Code, Cursor, Copilot, or any AI coding agent:
- It re-discovers your architecture from scratch
- It proposes changes that were already debated and rejected
- It re-introduces bugs that were already fixed
Your CLAUDE.md / .cursorrules helps, but it's static and gets stale.
The Solution
Facts tell agents how things work. Decisions prevent re-debating. Regressions prevent re-breaking. Preferences teach agents how you code.
Quick Start
With an API key (Claude Code, terminal workflows)
One command: sets up global profile, creates .context/, configures Claude Code + Cursor, runs AI analysis, prints CLAUDE.md instructions.
With Cursor (no API key needed)
This installs everything Cursor needs:
- MCP server in
~/.cursor/mcp.json(auto-starts repomemory in every project) - Rules in
.cursor/rules/repomemory.mdc(teaches Cursor's AI to use context) - 6 commands in
.cursor/commands/(run with/in Cursor chat)
Then in Cursor chat, type:
Cursor's own AI scans your repo and populates .context/ via the MCP tools. No external API key required — your Cursor subscription handles it.
Available Cursor commands:
Guided wizard
Walks through provider selection, tool integration, and first analysis. If no API keys are detected, offers a "None — I use Cursor" option that skips external analysis entirely.
Non-interactive (CI-safe)
No prompts when --yes / --defaults / --no-prompt is used.
MCP Server — Agents With Real Memory
The real power is the MCP server. When configured via repomemory setup claude, it auto-starts with Claude Code and gives agents 7 tools:
Sessions are auto-captured on shutdown. Zero config — repomemory setup claude handles everything.
Supported Tools
Cursor users: You don't need any API key. Run
npx repomemory setup cursor, then use/repomemory-analyzein Cursor chat. Cursor's AI does the analysis using the MCP tools — whatever model Cursor is using (it can even switch models mid-task).
Supported Providers
Embeddings (optional, for semantic search): Gemini text-embedding-004 (free, default) or OpenAI text-embedding-3-small. Auto-detected from available API keys.
All Commands
Configuration
.repomemory.json in your repo root (all fields optional):
Custom ignorePatterns and keyFilePatterns are additive — they extend built-in defaults, not replace them.
Why Not Just CLAUDE.md?
repomemory doesn't replace CLAUDE.md — it complements it. CLAUDE.md is for instructions and rules. .context/ holds the knowledge that grows over time.
Contributing
See CONTRIBUTING.md for development setup, testing, and contribution guidelines.
License
MIT
Built for developers who are tired of AI agents forgetting everything between sessions.
来源:README.md,提交 b5b9d25
工具
0版本历史
1- v1.3.0最新Sep 16, 2026
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