xkcd Comic Suggester

xkcdai

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/.

How it works

xkcd JSON API ─┐               ├─► comics.json + explain.json ─► embeddings.npy ─► find_xkcd ─► Claudeexplainxkcd  ──┘        (cache)                    (bge-small)     (cosine)    (mentions it (transcripts +                                                                 if it fits)  explanations)

• Data: title + mouseover alt from the official API, plus the community transcript and explanation from explainxkcd.com. The explainxkcd context is essential: the official API dropped transcripts around comic ~1675, so without it the most-shared modern comics (e.g. #2347 Dependency) are unmatchable — their joke text lives only inside the image.
• Embeddings: 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).
• Search: a normalized numpy matrix + dot product. No vector DB needed for a few thousand comics.
• Restraint: because xkcd has a comic for almost everything, a similarity cutoff alone can't judge relevance. 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.

Use the deployed MCP server (as custom connector)

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):

1. Settings → Connectors → Add custom connector.
2. Paste the connector URL, including the /mcp path: https://xkcdai.onrender.com/mcp
3. Leave OAuth blank (this server needs no auth) and click Add.
4. The connector's find_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

• The server is public and unauthenticated — fine here (read-only comic search, no secrets). Don't reuse this pattern for anything sensitive without OAuth.
• Hosted from this repo via the Dockerfile and render.yaml; pushes to main auto-redeploy.
• GET /healthz reports liveness, whether the index is loaded, and current RSS — handy on a 512 MB instance:
  bash

  curl https://xkcdai.onrender.com/healthz

Local setup

python -m venv .venv# Windows (PowerShell):  .venv\Scripts\Activate.ps1# macOS/Linux:           source .venv/bin/activatepip 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"

Use locally as an MCP server

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.

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 Code — your global ~/.claude/CLAUDE.md (applies everywhere) or a per-repo CLAUDE.md; restart the session to load changes.
• Claude.ai / Claude Desktop — Settings → Profile → "What personal preferences should Claude consider in responses?" (every plan, including free; syncs to the mobile app). Each person who uses the connector adds it in their own account.

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 thetopic. 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 silentWhen you share one, give just that single comic: its number and title, its URL, andquote 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.

Not just Claude — works with any MCP client

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:

• stdio: run xkcdai-server locally (see Use locally as an MCP server), or
• HTTP: the deployed URL https://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).

Configuration

• 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.

Maintenance

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.

Credits & licensing

This project bundles content from two sources, each under its own license, so the code and the data are licensed separately:

• Code (src/, Dockerfile, etc.) — MIT.
• Comics & mouseover text — © Randall Munroe / xkcd, licensed CC BY-NC 2.5: non-commercial, with attribution.
• Transcripts & explanations (cached in data/) — from explainxkcd.com, licensed CC BY-SA 3.0: redistributed here under the same license, with attribution.

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.