Context7
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作者提供的说明(英文原文)
Suggests a relevant xkcd comic during a conversation, via semantic search over every comic.
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 …”。
适用于网页版、桌面版和手机版 Claude:
https://xkcdai.onrender.com/mcp在终端中运行这条命令
claude mcp add --transport http xkcdai https://xkcdai.onrender.com/mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"xkcdai": {
"url": "https://xkcdai.onrender.com/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": {
"xkcdai": {
"type": "http",
"url": "https://xkcdai.onrender.com/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。
ChatGPT 只能连接互联网上的服务器:
https://xkcdai.onrender.com/mcp菜单名称可能因套餐和版本不同而略有差异。
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。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
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 papjuli 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
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
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。
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(0.2.0)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
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
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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。
An MCP server that surfaces the right xkcd comic during a conversation, if one is relevant.
Live connector:
https://xkcdai.onrender.com/mcp— add it in claude.ai →
Settings → Connectors. See Use the deployed MCP server.
It builds a semantic index over every xkcd comic (title + mouseover text + transcript) using on-device embeddings, then exposes a single find_xkcd tool. A Claude conversation can call it whenever the topic feels xkcd-shaped; a relevance threshold means weak matches return nothing, so it stays quiet instead of forcing a tenuous reference.
The fetched transcripts, explanations, and the embeddings are currently committed in this repo, under data/.
xkcd JSON API ─┐
├─► comics.json + explain.json ─► embeddings.npy ─► find_xkcd ─► Claude explainxkcd ──┘ (cache) (bge-small) (cosine) (mentions it (transcripts + if it fits) explanations)
fastembed (ONNX) with BAAI/bge-small-en-v1.5 — local, free, offline after first download, no PyTorch. Swap the model in src/xkcdai/embed.py (e.g. BAAI/bge-base-en-v1.5 for marginally better ranking at ~3× the size).min_score (default 0.62) is just a coarse floor; the real "should I bring this up?" decision is made by the calling model, guided by the score bands documented on the find_xkcd tool.The server is deployed at https://xkcdai.onrender.com on Render. Add it as a Claude custom connector to use it in the Claude web and mobile apps (note: the Free plan only allows one custom connector). Anyone can add the same URL in their own account.
In claude.ai (web — do this once; it then syncs to the mobile app):
https://xkcdai.onrender.com/mcpfind_xkcd tool is now available in chats, on desktop and phone. For Claude to suggest comics on its own, also add the instruction from Make Claude suggest comics proactively to your Profile preferences.Notes
main auto-redeploy.GET /healthz reports liveness, whether the index is loaded, and current RSS — handy on a 512 MB instance: curl https://xkcdai.onrender.com/healthz
python -m venv .venv
pip install -e .
xkcdai build
Add --no-enrich to skip the explainxkcd fetch (faster/offline, weaker matches).
Test it from the command line:
xkcdai search "my code finally compiled after an hour"
xkcdai search "arguing about the correct date format" xkcdai search "spent more time automating it than doing it by hand"
The server runs over stdio. Point your MCP host at it.
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": { "xkcdai": { "command": "C:\\your\\path\\to\\xkcdai\\.venv\\Scripts\\xkcdai-server.exe", "env": { "XKCDAI_DATA_DIR": "C:\\your\\path\\to\\xkcdai\\data" } } } }
Claude Code (-s user makes it available in every project, not just this folder):
claude mcp add xkcdai -s user -e XKCDAI_DATA_DIR=C:\your\path\to\xkcdai\data -- C:\your\path\to\xkcdai\.venv\Scripts\xkcdai-server.exe
Always set XKCDAI_DATA_DIR, since the host launches the server from an arbitrary working directory.
MCP only gives Claude the *ability* to call
find_xkcd— it won't volunteer
comics on its own. See Make Claude suggest comics proactively.
Connecting the server only gives Claude the *ability* to call find_xkcd; it won't reach for it unprompted. To make Claude volunteer comics, paste the instruction below wherever that Claude reads persistent instructions:
~/.claude/CLAUDE.md (applies everywhere) or a per-repo CLAUDE.md; restart the session to load changes.When a conversation naturally lands on a topic xkcd is known for — programming,
science, math, statistics, engineering, the absurdity of standards, relationships, everyday life — call the find_xkcd tool (xkcdai) with a short phrase describing the topic. Then judge whether to bring it up:
When you share one, give just that single comic: its number and title, its URL, and quote the alt (mouseover) text — that's half the joke. At most one comic per topic, and never force a tangential reference. When in doubt, say nothing.
It's still Claude's judgment, so it won't fire on every borderline topic — asking *"is there an xkcd for this?"* always triggers a lookup.
The examples above use Claude, but find_xkcd is a standard Model Context Protocol tool, so any MCP-capable host can use it. Point the client at either transport:
xkcdai-server locally (see Use locally as an MCP server), orhttps://xkcdai.onrender.com/mcp.The server is LLM-agnostic internally, too: matching runs on a local embedding model. Only the host-specific bits differ — how you register the server, and where you put the "suggest a comic when it fits" instruction (each client has its own system-prompt / rules mechanism, e.g. Cursor Rules or a VS Code .instructions file).
XKCDAI_DATA_DIR — where comics.json, explain.json, embeddings.npy, and index.json live.find_xkcd(context, max_results=3, min_score=0.62) — lower min_score for more (looser) suggestions, raise it to be stricter.Re-run xkcdai build periodically to pick up new comics — it incrementally fetches new comics and their explainxkcd context, then re-embeds:
xkcdai build
Use --force to rebuild everything from scratch, or --no-enrich to skip the explainxkcd fetch. xkcdai enrich fetches only the explainxkcd context.
This project bundles content from two sources, each under its own license, so the code and the data are licensed separately:
src/, Dockerfile, etc.) — MIT.Because data/ mixes xkcd's NonCommercial content with explainxkcd's ShareAlike content, treat the data as non-commercial and keep any redistribution under these terms. The MIT license covers the source code only — not data/. At runtime, find_xkcd results link back to both xkcd and explainxkcd for per-item attribution.
This is an unofficial fan project, not affiliated with or endorsed by xkcd or explainxkcd.