Context7
作者：upstash
Up-to-date docs for AI agents
电脑或云端★ 64,224MIT今天更新
安装
Commons
概览
作者提供的说明（英文原文）
Shared memory, work claims and handoffs so parallel AI coding sessions stop colliding.
PopNx MCP 的三大支柱
这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
- 使用情况i尚未统计★ –
它能帮你做什么
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
- 连接方式: 在你的电脑上运行
- 传输方式: stdio
- 分类: 搜索与 AI 记忆
安装
选择你使用的 AI 应用，然后复制设置。
安装之前
- 基础检查：1 项中通过 1 项
- 在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
- 需要你自己填写：
COMMONS_AGENT,COMMONS_TOOLS
你需要
- Docker已安装 Docker
你用的是哪个应用？
在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"commons-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.37.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add commons-memory --env COMMONS_AGENT=your-value --env COMMONS_TOOLS=your-value -- docker run -i --rm -e COMMONS_AGENT -e COMMONS_TOOLS ghcr.io/neoo-blue/commons-memory:0.37.1 serve --transport stdio运行前请先填写空着的值。
或者自己复制设置
粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json
{
"mcpServers": {
"commons-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.37.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "your-value"
}
}
}
}浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。
或者自己复制设置
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"commons-memory": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"COMMONS_AGENT",
"-e",
"COMMONS_TOOLS",
"ghcr.io/neoo-blue/commons-memory:0.37.1",
"serve",
"--transport",
"stdio"
],
"env": {
"COMMONS_AGENT": "your-value",
"COMMONS_TOOLS": "your-value"
}
}
}
}浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。
这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上，无需账户。
需要你填写的值
COMMONS_AGENTenvName this client goes by in CommonsCOMMONS_TOOLSenvTool listing: lite, core or all
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。
它能做什么
它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。
基础检查i
我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 Neoo-Blue 验证，该账户拥有此仓库
- … 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
- … 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
- – 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表
与“搜索与 AI 记忆”中的其他服务器比较i
- 星标数多于此分类中其他 7258 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 7258 个服务器的 99% 更新
- 基础检查结果等于或优于此分类中其他 7258 个服务器的 100%
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。
常见问题
Commons 安全吗？
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。
它需要哪些密钥或代码？
注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。
它在我的电脑上运行还是在云端？
它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。
它还在维护吗？
GitHub 仓库最后更新于–，最新版本（0.37.1）于今天进入注册中心。
哪些应用可以使用它？
支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。
有什么可以替代它？
同一分类中有：Context7, Codebase Memory, Exa
替代选择
同一分类中其他作者的服务器，按星标数排序。
如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Codebase Memory
作者：DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
在你的电脑上运行★ 48,148MIT20天前更新
安装
Exa
作者：exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
在云端运行★ 5,213MIT上个月更新
安装
作者的 README
打开 README
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Commons
Run several Claude Code sessions at once without them redoing or overwriting each other's work.
Each session (say, one per git worktree) checks in with Commons before it starts a task. If another session already has it, it hears so and backs off. Finished work, decisions and handoffs are shared, so the next session builds on them instead of starting over. Everything lives in one local SQLite file: no API keys, no account, no telemetry.
/plugin marketplace add Neoo-Blue/commons-memory/plugin install commons@commons-memory
Needs uv. Each folder is one agent (claude-code@ ), so run parallel sessions in separate worktrees or checkouts with different folder names.
Two sessions, two worktrees, same task:
claude-code@payments-fix start_work("fix the payments retry", paths=["pay.py"])-> ok: it's yours, others are warned off claude-code@billing-ui start_work("fix the payments retry", paths=["pay.py"]) -> busy: claude-code@payments-fix has it since 02:33. msg_send them to split it, or wait for their finish_work.
It works alongside claude-mem and Claude Code's own memory: those help one session remember, Commons keeps several sessions from colliding. The plugin lists 19 tools (memory and coordination only). Credential and vault tools are not listed and nothing asks for a key; they stay reachable through call() only if you set up a vault yourself. How it stays safe: docs/threat-model.md.
Beyond one machine: the hub
The same Commons runs as a small self-hosted hub, so sessions on different machines, and other AIs (Codex, Cursor, Gemini CLI, ChatGPT, Grok), share one view of who is doing what.
Commons is a self-hosted memory and coordination hub that every AI connects to over MCP. It works with Claude, ChatGPT, Grok, Cursor, Codex, Gemini and your own agents. They share memory, pick up each other's unfinished work, message and wake each other, learn how *you* like things done, and split big jobs into reviewed, debated, budgeted subtasks. One SQLite file (or Postgres) holds it all. A dashboard shows who is doing what and what it costs.
curl -fsSL https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.sh | shirm https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.ps1 | iex # WindowsDocker: see docs/docker.md. Prefer to read it first? curl -fsSLO https://raw.githubusercontent.com/Neoo-Blue/commons-memory/main/install.sh && less install.sh && sh install.sh. No-script alternatives: uvx --from git+https://github.com/Neoo-Blue/commons-memory commons init (run without installing) · uv tool install "commons-memory[http] @ git+https://github.com/Neoo-Blue/commons-memory" · pipx install "commons-memory[http] @ git+https://github.com/Neoo-Blue/commons-memory"
Contents
Quickstart · Feature tour · Architecture · Connect any AI · Screenshots · Multi-agent · Security · Networking · Configuration · Troubleshooting · FAQ · Comparison · Roadmap · Changelog
Onboarding (self-hosted hub)
- Copy
.env.exampleto.env, create the three secret files it lists (dashboard token, Postgres password, vault key), thendocker compose up -d(docker-compose.yml; the comments explain every option). - Open the dashboard and go to Setup. A checklist shows what is missing:
- provider keys: TypeSafe (Jev), Anthropic, OpenAI, Google, xAI, OpenRouter, or a local Ollama;
- the decision agent's fallback order;
- your service credentials;
- features, all on by default.
Keys are stored encrypted in the vault and never shown again.
- Add an AI on the Connect page: one terminal line connects every AI on a machine, one sentence connects a bot, one address connects a chat app. No key is copied anywhere, and every AI it connects can be woken the moment work arrives.
- Each agent hands over its memories, keys and scheduled tasks; Setup shows who still owes what.
2-minute quickstart
# 1. install (above) — this also runs `commons init` (~/.commons/commons.db)2. connect your first AI: registers it, saves its key, installs its skill + MCP config
commons connect claude --platform claude-code # or: cursor | codex | claude-desktop | grok | generic
3. use it — from the CLI or from the AI ("remember that…", "what did we decide about…")
commons remember "Payments use Stripe webhooks; retries are idempotent" --project shop commons search "how do payments retry"
4. watch everything (no token needed on localhost)
commons dashboard # http://127.0.0.1:8766
Connect a second AI the same way and it can see the first one's memory immediately. Each client lists only the 32 core tools (6.1k tokens, against 40.4k for all 186); `tools(query)` finds the other 154 and `call(tool, args)` runs them. For other AIs (ChatGPT, Grok, Muse…), paste [the universal prompt](#connect-any-ai).Feature tour
| Area | What you get | Learn more |
|---|---|---|
| Infrastructure map | One layered map of where everything runs and how it connects: machines, LXCs and VMs, containers, services, URLs and ports, tunnels, storage and bind mounts, repos, systems (e.g. Plex: its parts and the guest each runs on) and the vault credential each uses (name only). Built from a read-only collector (commons infra collect --submit, or commons infra install to run it on a schedule) and from your memories (a small model extracts stated facts, each citing its notes), merged by vmid, IP and URL. Zoomable map, inventory and drawers on the dashboard; agents ask infra("plex") | docs/guide.md |
| Memory & knowledge | Hybrid search (BM25 + local fastembed vectors, entity/time/recency signals, optional rerank) with token budgets · context=N returns the turns around each short hit (a reply needs the turn it answers; a long turn stands alone) and relative dates resolve against each memory's own date ("yesterday (7 May 2023)") · free-text contradiction flags (TypeSafe) · auto-capture hooks for Claude Code/Codex/Gemini/Cursor that keep every message and reply verbatim plus typed observations, and a turn hook for chat apps without hooks (docs/hooks.md) · one graph linking memory, code, sessions, agents · code index (Python, JS/TS, Go, Rust, Java, Ruby, C, C++, C#) plus live definitions, references and types from each language's own server (code_lookup, LSP) · Graphiti adapter (mirror memories into a temporal knowledge graph, bring its facts back) · conflict detection · auto-built, cited knowledge base per project · librarian that tidies and answers find() | docs/tools.md |
| Project board | Every request you make, in your words, with the targets (metric, goal, current), expectations, actions and deliveries under it, layer by layer (project / ui/dashboard). Done needs evidence, dropped needs a reason, and asking twice is counted. It leads every agent's check-in, so nothing you asked for is lost to context compaction or an agent switch. Agents' questions for you wait under "Needs you" and your answer goes straight back to them | docs/tools.md |
| No duplicate work | start_work checks every task against what other agents are doing now and what was finished, so two agents never build the same thing and nobody redoes finished work; hooks run the same check on every message. Each agent gets the Commons routine on its first check-in, so you never have to explain it | PROMPT.md |
| Credential vault | Commons stores your API keys and logins encrypted and makes calls for agents, so no agent ever sees a key, and a key only ever goes to its own service. A decision agent rules on each request: sound reads are allowed, writes need your request behind them, anything destructive or costly comes to you as an approval link the agent hands you: one page showing the exact request, approved with your owner password (agents can't), and approving runs it. Or switch on "approve everything" at your own risk, or always allow one key. It is an order you choose (TypeSafe, any provider you have a key for, a live connected agent on its own subscription, then you), and a phone notification with Yes / No buttons lets you answer anywhere. Agents creating accounts get a generated username and password from the vault · an agent deposits a key the moment it gets one; the base URLs it may go to can follow, and until then it goes nowhere · each key records what it is for, what it can do at the provider, and every place it is installed or used, linked on the infrastructure map, so it can be rotated or narrowed without guessing | CHANGELOG.md |
| Team awareness | A live Team now view (who is working, blocked, done or waiting on you) · a card per agent that the hub writes from what it can check (who issued its key and when, where it runs, how it is woken, its usage headroom, its schedules, the work it finished), kept apart from what the agent claims, with who(name) to read it · agents meet a newcomer at their next check-in instead of a broadcast that would wake and bill every agent, and a newcomer gets the whole team at its first · display names only you set, so grok reads as "Grok bot" while messages still reach it, and no agent can name itself after another · introductions you ask for: one note to each, nobody else woken · every release tells all agents what changed and what to adapt · handoffs carry a commit Commons checks on GitHub · failed CI runs, new issues and new PRs (GitHub watcher or webhook) become jobs for the best live agent | CHANGELOG.md |
| Continuity | Sessions, checkpoints, handoffs that resume in another AI · layered context packs (L0 gist → L3 full) so the next AI doesn't re-pay tokens · decisions with rationale and why() · leftovers and recurring jobs | docs/guide.md |
| Teamwork | Submit a task and it is split for the team: a model plans it (Haiku by default), else a live agent does, else keyword rules, sized to who is live, what each agent is good at and its usage left. Big hand-offs are planned too, and an agent can split a subtask it holds and merge the parts. Six-stage workflow (submit_task(pattern="sdlc") or /sdlc, or one stage with /spec /plan /build /test /review /ship): you approve the spec and confirm the release from the board or your phone, stage leads hand out task cards up to 3 levels deep, each card goes to a cheap, mid or top model and effort by difficulty x criticality (on the agent's own CLI), and the Workflow page shows the stage spine, the agent tree, traceability and tokens saved. Patterns: plan → parallel parts each gated by a review → summary; work → cross-review (author ≠ reviewer); debate → judge; consensus vote. Every job has a shared workspace: each part's result, the code it changed (diff, commit checked on GitHub, also captured by the hooks) and any files, on one timeline with an agent filter. Pin a step to a named agent (retries stay with it), quality gates, budgets, leases with automatic reassignment, an escalation ladder, routing to the right agent + model + effort by strengths, past success, speed, price and usage left, multi-project scheduling, task breakdown view | docs/guide.md, docs/multitasking.md |
| Limits & schedules | Each agent's 5-hour a
只显示了开头部分；其余内容请在仓库中阅读