Server data from the Official MCP Registry
Suggests a relevant xkcd comic during a conversation, via semantic search over every comic.
Suggests a relevant xkcd comic during a conversation, via semantic search over every comic.
Remote endpoints: streamable-http: https://xkcdai.onrender.com/mcp
Valid MCP server (1 strong, 4 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
Endpoint verified · Open access · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: XKCDAI_DATA_DIR
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-papjuli-xkcdai": {
"url": "https://xkcdai.onrender.com/mcp"
}
}
}From the project's GitHub README.
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):
/mcp path: 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.python -m venv .venv
# Windows (PowerShell): .venv\Scripts\Activate.ps1
# macOS/Linux: source .venv/bin/activate
pip install -e .
# Fetch comics + their explainxkcd context, then embed (downloads the model once).
# First run ~10 min; re-running later only fetches what's new.
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:
- score >= 0.75 — strong match; mention it if it fits the moment
- 0.66-0.75 — only if it genuinely lands
- below that — stay silent
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.
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