Afterpaths

io.github.burnssa由 GitHub 账号 burnssa 发布v0.2.5更新于 Oct 25, 2026

Session memory for AI coding agents. Search past sessions, extract rules, and track what works.

已验证STDIO仅桌面知识与记忆开发者工具

概览

AI 生成的概览

本地 MCP 服务器,让 AI 编程助手访问过往编程会话历史:列出、读取、搜索和总结会话,并提取可复用的规则。

可以做什么
列出 Claude Code、Cursor 和 Codex 的近期会话以便恢复上下文,读取会话摘要或原始记录,并查看带来源信息的文件写入/编辑清单。跨过往会话搜索,摘要无结果时自动升级到原始记录。生成会话的 LLM 摘要,并获取提取出的规则,涵盖死路、决策、陷阱和模式。
适用场景
适合同时使用多个 AI 编程工具、希望助手回忆早前会话、避免重复已知死路,或把项目规则带入新会话的开发者。适合想把会话历史和提炼经验作为原生工具而非单独命令行使用的人。
运行要求
以 Python 包形式通过 stdio 本地运行(uvx 或 pip,需 mcp 附加组件)。总结功能需要 ANTHROPIC_API_KEY 或 OPENAI_API_KEY;搜索、列表、查看和规则工具无需密钥。从本地 Claude Code、Cursor 和 Codex 存储读取会话数据。
安装前请注意
总结功能会用你的 API 密钥把会话内容发送给 Anthropic 或 OpenAI,可能产生费用。Cursor 支持不完整,部分会话可能返回空结果。生成的规则文件会写入项目,若在手动标记之外编辑可能阻止运行;源代码本身不会被修改。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Afterpaths,将其添加到工作区。
  2. 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

Afterpaths

Smarter with every session, automatically.

Extract rules from what worked. Track what didn't. Find the best models for your stack.

You're running Claude Code, Cursor and Codex, but which model actually works best for your stack? What approaches lead to breakthroughs vs. expensive dead ends? How do you stop your agents from making the same mistakes?

Afterpaths gives you a single view across all your AI coding tools: compare what's working, capture discoveries as rules, and guide your agent team away from costly diversions.

[Afterpaths Demo]

What you're seeing:

  1. ap audit — Overview of your sessions, models used, and rule status
  2. ap show 5 --raw — Raw session transcript (the messy JSONL data, made readable)
  3. ap show 5 — LLM-generated summary extracting discoveries, dead ends, and decisions
  4. head .claude/rules/gotchas.md — Rules automatically extracted and ready for Claude's next session

The Problem

You're managing multiple agents - retaining critical context and learning from sessions is painful:

  • Repeated mistakes — Your agents hit the same gotchas. Three weeks later, same dead end, same wasted tokens.
  • No cross-tool visibility — Is Opus actually better than Sonnet for your codebase? Is Cursor outperforming Claude Code? You're guessing.
  • Rules are tedious — After a costly diversion, the last thing you want is to write a CLAUDE.md rule. So you don't. And the knowledge evaporates.
  • Sessions vanish — Session content is obscurely logged and hard to extract. Then it's often auto-deleted after 30 days. That breakthrough architecture decision? Context gone.

Afterpaths captures sessions across tools, surfaces what's working, and generates rules automatically—so your agents learn from every session, and you retain all your rich session context.

How It Works

Your Sessions                      Afterpaths───────────────                    ────────────────────────────────────
Claude Code  ──► ap log      ──► Browse sessions across IDEsCursor           ap stats    ──► Analytics: tokens, activity, errorsCodex            ap summarize──► Session summaries (what happened)                 ap rules    ──► Rule files (what to remember)                 ap search   ──► Find past discussions & discoveries                                    │                                    ▼                           .claude/rules/ · .cursor/rules/                                    │                                    ▼                           Your next session is smarter

Quick Start

bash
pip install afterpaths
# Navigate to your project (rules are project-specific)cd ~/code/your-project
# Run audit to see what you haveap audit

The audit shows your sessions across all tools, model performance, and whether you have rules set up. No API key needed.

From there, the recommended flow:

bash
# 1. Browse sessions and find significant workap log
# 2. Summarize important sessions (requires API key)export ANTHROPIC_API_KEY="sk-ant-..."ap summarize 1
# 3. Extract rules from summaries → .claude/rules/ap rules
# 4. Search across past sessionsap search "database schema"ap search "auth" --deep    # also search raw transcripts
# 5. Track ongoing performanceap statsap stats --daily

Tip: ap is the short alias for afterpaths. Both work identically.

All commands support --json for structured output (e.g., ap log --json, ap show 1 --json, ap search "query" --json).

See docs/commands.md for the full command reference and recipes.

From Session to Rules

Real example: A bug causing 76 missing sessions became a rule that prevents the same mistake.

While building afterpaths, sessions for a project weren't showing up. The path (let's call it) /Users/Code/foo_bar was being decoded as /Users/Code/foo/bar. After investigation, we discovered Claude Code uses lossy path encoding—both / and _ become -.

The summary captured the discovery:

markdown
## Discoveries
- **Claude Code's path encoding is lossy**: Project paths in `~/.claude/projects/`  are encoded by replacing `/` with `-`, but underscores are ALSO converted to  hyphens. Three different paths encode identically:  - `/Users/Code/foo_bar` → `-Users-Code-foo-bar`  - `/Users/Code/foo-bar` → `-Users-Code-foo-bar`  - `/Users/Code/foo/bar` → `-Users-Code-foo-bar`

ap rules extracted it into .claude/rules/gotchas.md:

markdown
- **Claude Code lossy path encoding**: Claude Code encodes project paths by  replacing both `/` and `_` with `-`, making them indistinguishable when  decoding. When decoding, try underscore variants alongside hyphen variants  at each greedy step, preferring longer segments (single directories) over  nested paths.  _Source: 91b1ffbc_

Next time Claude works on path decoding in this codebase, it already knows about the lossy encoding—no need to rediscover it.

Why Afterpaths

WithoutWith Afterpaths
Discover gotcha, forget to document itap summarize captures it with full context
Hit the same issue 3 weeks laterRule in .claude/rules/ prevents it
No idea what's workingap stats shows tokens, sessions, error rates
Sessions scattered across IDEsap log unified view across Claude + Cursor
Learnings siloed per toolRules sync to .claude/rules/ and .cursor/rules/

What Gets Extracted

CategoryWhat it capturesExample
Dead EndsApproaches that failed"Don't use X because Y"
DecisionsArchitectural choices"We chose Redis over Postgres because..."
GotchasNon-obvious warnings"Watch out for X when doing Y"
PatternsTechniques that worked"For X, use pattern Y"

Each rule includes source session references so you can trace back to the original context.

Supported Tools

ToolStatusLocation
Claude Code✅ Ready~/.claude/projects/*.jsonl
Cursor⚠️ Partial~/Library/Application Support/Cursor/User/workspaceStorage/
Codex CLI✅ Ready~/.codex/

Known Limitations

Cursor sessions: the adapter reads several known chat/composer formats from state.vscdb (including workbench.panel.aichat.view.aichat.chatdata, composer.composerData, and allComposers), but Cursor changes its storage schema often and some sessions will return Entries: 0 even when the state.vscdb file is present. When this happens, ap show <ref> --raw and the afterpaths_show_session MCP tool emit a warning rather than silently returning empty. The raw file is untouched — if you need that session, opening state.vscdb directly with sqlite3 will still work.

Tool provenance features (ap show --artifacts, commit tracing, file activity) only cover sessions whose entries the adapter can read.

MCP Server

Afterpaths includes an MCP server that puts session history directly into your agent's tool list. Instead of relying on agents to discover the CLI, the MCP server makes session search, summaries, and rules available as native tools.

bash
# Install with MCP supportpip install afterpaths[mcp]
# Add to Claude Codeclaude mcp add afterpaths -- afterpaths-mcp
# Or run directlypython -m afterpaths.mcp_server

Tools exposed:

ToolDescription
afterpaths_list_sessionsList recent sessions for context recovery
afterpaths_show_sessionRead session summaries and transcripts
afterpaths_show_artifactsShow artifacts ledger: files written/edited with provenance
afterpaths_summarizeGenerate summaries for sessions
afterpaths_searchSearch across past sessions (auto-escalates to transcripts on 0 summary hits)
afterpaths_get_rulesGet extracted rules (dead ends, decisions, etc.)

Once configured, agents can ask "have we seen this before?" or "what were the dead ends?" and get answers from your session history.

Privacy

  • All local — Summaries and rules stay in your project
  • Your API key — Uses your Anthropic/OpenAI key
  • Read-only — Never modifies your source code
  • Gitignored — .afterpaths/ excluded by default

Storage

your-project/├── .afterpaths/           # Summaries (gitignored)│   ├── summaries/│   └── meta.json├── .claude/│   └── rules/             # Generated rules (commit these!)│       ├── dead-ends.md│       ├── gotchas.md│       └── patterns.md└── src/

Hand-edited notes in rule files

Each rule file is split into a manual section (preserved across ap rules runs) and an auto section (regenerated each run):

markdown
# Gotchas: Things to Watch For
<!-- afterpaths:manual:start -->_Add project-specific notes here — preserved across `ap rules` runs._<!-- afterpaths:manual:end -->
<!-- afterpaths:auto:start -->> Auto-generated by `afterpaths distill` | Updated: 2026-04-21 12:00> Sources: 3 session(s)
## Rules
- **Some extracted rule**: ...  _Source: abc12345_<!-- afterpaths:auto:end -->

Put hand-curated rules or project-specific reminders between the manual:start / manual:end markers — they'll survive every ap rules run. Content outside those markers (and outside the recognized boilerplate) blocks the run as a safety check. Pass --force to overwrite anyway, or wrap the content in manual markers to preserve it.

If you're upgrading from an earlier version and your rule files contain only auto-generated content, markers are inserted automatically on the next ap rules run with an empty manual section — no action required.

Roadmap

  • Claude Code session parsing
  • Cursor session support
  • Session analytics (tokens, errors, daily trends)
  • LLM summarization
  • Automatic rule extraction
  • Multi-target export (Claude, Cursor)
  • Codex CLI support
  • Cross-session search (ap search)
  • JSON output (--json flag)
  • MCP server for agent integration
  • Semantic search across sessions
  • Benchmarking and productivity insights

License

MIT


Manage your AI coding agents. Learn what works. Stop repeating mistakes.

来源:README.md,提交 1bdd717

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.2.5最新Sep 16, 2026

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