Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Search local AI conversations by file or phrase and recall source turns. Four read-only tools.
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。
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。
选择你使用的 AI 应用,然后复制设置。
你需要
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": {
"thoughtdag": {
"command": "npx",
"args": [
"-y",
"thoughtdag",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add thoughtdag -- npx -y thoughtdag mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"thoughtdag": {
"command": "npx",
"args": [
"-y",
"thoughtdag",
"mcp"
]
}
}
}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。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"thoughtdag": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"thoughtdag",
"mcp"
]
}
}
}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。
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。
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
注册名称已通过 GitHub 账户 chenxiachan 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
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。
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。
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)。
GitHub 仓库最后更新于–,最新版本(0.2.2)于40天前进入注册中心。
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 Node.js。
同一分类中有:Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
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。
Find the conversations that shaped a file.
npx thoughtdag why src/lib/api.ts
Indexes the agent sessions already on your machine (Claude Code, Codex, DeepSeek Harness, Pi) by the files each turn read, wrote or edited, and lists those turns: when, what changed, what was asked, what the answer said about the file. Every hit links back to the conversation.
~/.thoughtdag (0700/0600) and can be deleted with thoughtdag purge.Δ lines are observed changes; ≈ lines are read from the answer and are candidate explanations, not verified reasons.thoughtdag index [--full] [--canvas <dir>]
thoughtdag why [--include-read] [--all] [--limit N] [--json] thoughtdag why --check # one line, exit 0/1: is there history here? thoughtdag find " " [--in q|a|m] # where these exact words were asked, answered or attached thoughtdag recall thoughtdag status thoughtdag purge [--cache] thoughtdag mcp # the same questions as MCP tools (stdio, read-only) thoughtdag setup [mcp | rules [--remove]]
thoughtdag setup mcp registers the server for Claude Code in this project's .mcp.json and for Codex in the user-level ~/.codex/config.toml; the agent then has why_check, why_file, find and recall_turn as tools. thoughtdag setup rules adds two lines to this project's CLAUDE.md and AGENTS.md — check for history before editing a file; query before explaining why code is the way it is — as a marked block, --remove takes it out. Rule changes are per project and explicit; nothing is written unless you ask.
The server's MCP Registry name is io.github.chenxiachan/thoughtdag. A client that supports local stdio servers can start it with:
{
"mcpServers": { "thoughtdag": { "command": "npx", "args": ["-y", "thoughtdag@0.2.2", "mcp"] } } }
Requires Node.js 20 or newer and supported session logs on the machine running the server. Start it in the relevant project directory so file queries use the intended workspace. Clients use different configuration formats; the example above is for clients that accept mcpServers JSON.
The four tools search and recall history; they cannot edit a canvas, modify source sessions, or replace the client's conversation. Derived indexes and caches are written under ~/.thoughtdag. Retrieved text is returned to the calling agent and may enter that agent's model context; review the client's provider settings before using private history.
The Dockerfile installs the published CLI version as a non-root stdio server. It does not copy the repository or any session data into the image. From the repository root:
docker build -f cli/Dockerfile -t thoughtdag-mcp cli
docker run --rm -i --network none thoughtdag-mcp
An empty container answers MCP initialization and tools/list; history queries have no results until you explicitly provide local data. No model key, private session, or hosted endpoint is needed for the directory check.
Glama generates its own Dockerfile from the listing's Admin → Dockerfile form. Use Node.js 22 and these build steps:
["npm install --global --ignore-scripts --no-audit --no-fund thoughtdag@0.2.2"]
Use these CMD arguments (Glama adds its own mcp-proxy wrapper):
["env", "THOUGHTDAG_HOME=/tmp/thoughtdag-index", "THOUGHTDAG_SESSION_ROOTS=/data/sessions", "THOUGHTDAG_CANVAS_ROOTS=/data/canvases", "THOUGHTDAG_MEMORY_ROOTS=", "thoughtdag", "mcp"]
Leave placeholder credentials empty, then build and release. The repository root builds the web frontend; it does not produce dist/thoughtdag.mjs. Keep the pinned CLI version in this configuration aligned with the version you intend to list. Glama's generated image is separate from the non-root image above.
For actual local use, mount only the history directories you choose, read-only, at /data/sessions and optionally /data/canvases. The derived index is stored separately at /home/node/.thoughtdag. Query absolute artifact paths recorded in those sessions; the container's default working directory is not your host project's path. The native npx configuration above is the simpler option for project-relative queries. A cloud-hosted copy cannot see the history on your computer.
The repository also contains a Codex skill for opening a session in the desktop app or running CLI history queries:
npx skills add chenxiachan/thoughtdag --skill thoughtdag --agent codex
This installs a skill in the current project. Opening a session needs the ThoughtDAG desktop app or its local bridge; CLI queries use the npm package. It is separate from MCP registration and does not provide a canvas-writing MCP tool.