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 it on the web or phone.

It builds a local 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.

How it works

xkcd JSON API ─┐
               ├─► comics.json + explain.json ─► embeddings.npy ─► find_xkcd ─► Claude
explainxkcd  ──┘        (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.

Related MCP server: mediawiki-mcp-server

Setup

python -m venv .venv
# Windows (PowerShell):  .venv\Scripts\Activate.ps1
# macOS/Linux:           source .venv/bin/activate
pip install -e .

# 1. Fetch every comic's metadata.
# 2. Fetch transcripts + explanations from explainxkcd (~2 min, be patient & polite).
# 3. Build the embedding index (downloads the model once; ~5-8 min to embed).
# Re-running later only fetches what's new.
xkcdai build          # fetch comic metadata
xkcdai enrich         # fetch explainxkcd context
xkcdai build          # embed everything into the index

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 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:\\Users\\papju\\claude\\xkcdai\\.venv\\Scripts\\xkcdai-server.exe",
      "env": { "XKCDAI_DATA_DIR": "C:\\Users\\papju\\claude\\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:\Users\papju\claude\xkcdai\data -- C:\Users\papju\claude\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 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.

Use it on the web or phone (custom connector)

The server is deployed at https://xkcdai.onrender.com. Add it as a Claude custom connector to use it in the Claude web and mobile apps (custom connectors work on every plan; Free allows one). 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.

To share it, send someone https://xkcdai.onrender.com/mcp and have them repeat steps 1–4 in their own Claude account.

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.

• The free Render instance sleeps when idle, so the first request after a nap is slow (cold start + model load), then snappy.

• Hosted from this repo via the Dockerfile and render.yaml; pushes to main auto-redeploy.

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

Pick up new comics periodically (both steps are incremental):

xkcdai enrich     # new explainxkcd context
xkcdai build      # fetch new comics + re-embed

Use xkcdai build --enrich to do both in one go, or --force on either command to rebuild everything from scratch.