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Record Demo

OrganizationPopular
apify
record-demo

Record or regenerate the mcpc demo GIFs (the README hero docs/images/mcpc-demo.gif and the focused tapes in docs/vhs/) with VHS. Use whenever asked to create, refresh, restyle, shorten, or fix a terminal demo/animation/GIF of mcpc. The tapes drive real mcpc commands; for the authenticated step this skill ALWAYS prompts for a short-lived, low-permission TEST token first (never production). Captures the VHS + mcpc gotchas learned the hard way — read it fully before editing a tape.

Overview

Publisherapify
Repositorymcpc
Skill namerecord-demo
Stars
1K
Forks
98
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by apify on GitHub. Read the source before you install it.

Installation

Install the Record Demo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/apify/mcpc/tree/main/skills/record-demo
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/apify/mcpc.git /tmp/mcpc
mkdir -p .claude/skills
cp -r /tmp/mcpc/skills/record-demo .claude/skills/record-demo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Record Demo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Record Demo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Record Demo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

record-demo: VHS demo GIFs for mcpc

The tapes in docs/vhs/*.tape are VHS scripts that drive a real shell session — VHS types each command, runs it against a live MCP server, captures the terminal, and renders a GIF. The README hero is docs/images/mcpc-demo.gif, built from docs/vhs/mcpc-demo.tape.

This file is the accumulated know-how. Read all of it before touching a tape — most rules below were discovered by hitting the wall, and skipping them wastes whole render cycles (~1–2 min each).

The hero flow (mcpc-demo.tape)

A basic-use story across both transports:

  1. mcpc — empty state (no sessions, no profiles)
  2. mcpc connect mcp.json:filesystem — local stdio server (auto-names @filesystem)
  3. mcpc — session list (now shows the live session)
  4. mcpc @filesystem tools-list
  5. mcpc @filesystem tools-list --json — JSON output, syntax-highlighted, no jq
  6. mcpc connect mcp.apify.com -H "Authorization: Bearer $APIFY_TOKEN" — remote HTTP server (auto-names @apify)
  7. mcpc @apify tools-list
  8. mcpc @apify tools-get search-actors — inspect one tool's input schema
  9. mcpc @apify tools-call search-actors keywords:="web scraper" limit:=3
  10. mcpc @apify close

Ten commands run ~45s; there is no hard 30s cap for this flow.

Style conventions (the current standard — match these)

  • No # comments in the visible script. The commands are self-descriptive.
  • No | head, no 2>/dev/null on visible commands. Show real output even if long — it scrolls naturally. (connect ≈ 86 lines incl. an "Available commands" list, tools-call search-actors ≈ 56, filesystem tools-list --json ≈ 300.)
  • Continuous session — never clear between steps. Put a single blank-line Enter before each command (after the first) so it's separated from the previous output, like a real terminal session.
  • Colored prompt + bold-white typed commands. In the hidden setup block:
    Type 'export PS1="\[\e[1;38;2;25;230;77m\]$\[\e[0m\] \[\e[1;97m\]"'
    Enter
    Type "trap 'tput sgr0' DEBUG"
    Enter
    • PS1 is a bold bright-green $, then ends with \[\e[1;97m\] so the typed input renders bold bright-white.
    • The DEBUG trap runs tput sgr0 before every command so the bold-white input does not bleed into command output.
  • Empty state needs a clean home — hidden: Type 'export MCPC_HOME_DIR="$(mktemp -d)"' so mcpc shows "No active MCP sessions / No OAuth profiles".
  • Color is automatic for non-piped commands — mcpc detects the TTY and emits color (256-color, plenty vivid). You only need export FORCE_COLOR=3 (+ COLORTERM=truecolor for exact hex) when a command is piped (mcpc turns color off when stdout isn't a TTY). The current tapes avoid pipes, so they don't need it. (The CLI palette lives in src/cli/output.ts, RAINBOW_SATURATION, bumped to 78% for vividness — that's where the demo colors come from.)

VHS gotchas (these will bite you)

  • ASCII prompt symbols only. Multibyte glyphs (❯, », ▶) break bash prompt rendering under VHS and show up as garbage like 92m]. Use $ (or >), styled with color + bold.
  • Type quoting: use single quotes around any command containing double quotes. A \" inside a double-quoted Type breaks VHS's parser. e.g. Type 'mcpc @apify tools-call search-actors keywords:="web scraper" limit:=3' and Type 'export PS1="\[\e[…m\]$\[\e[0m\] "'.
  • Output/Screenshot paths: must not start with a digit (Output 1-foo.gif fails to parse) and must not be long absolute paths (the parser chokes). Use short, letter-leading, relative names and run vhs from docs/vhs/.
  • Screenshot is unreliable (frequently exits 2 even though the GIF rendered fine). Don't depend on it — pull frames from the finished GIF instead: ffmpeg -y -ss <seconds> -i x.gif -vframes 1 frame.png, then Read the PNG.
  • Renders are slow (~1–2 min each: real-time timeline + Chromium + ffmpeg encode). Render tapes one at a time — a for loop over several blows the 5-minute command timeout. Extracted frames often land mid-typing; sample a few timestamps around when output should be on screen.
  • Hidden connects leak into the recording if bash falls behind. When a tape connects in the hidden setup (so the feature commands run against a ready session, e.g. tools/scripting/grep), a slow connect lets VHS type ahead; bash then echoes the buffered commands and runs the clear after Show, so the setup spills into frame. Pattern that works: type the connect(s), then one generous Sleep (7–8s) so they finish, then clear, then another Sleep (~1.5s) before Show. (Tapes that connect visibly as their first command don't need this — their hidden setup is just fast exports + clear.)

Stdio servers in a headless / proxied box

  • npx-launched stdio servers are too slow here. npx -y <pkg>'s registry round-trip exceeds mcpc's 60s connect handshake, so connect times out (MCP error -32001). Fixes: pre-install the server (npm i -g <pkg>) and put the direct binary in mcp.json (e.g. mcp-server-filesystem, starts in ~0.3s — also a cleaner session header), or use npx --prefer-offline -y <pkg> once the npm cache is warm (~5s; plain npx -y still does the slow registry check even when cached).
  • Puppeteer does NOT work for headless recording. @modelcontextprotocol/server-puppeteer launches Chromium eagerly on startup and hangs/times out as root in the container. Use @modelcontextprotocol/server-filesystem instead (14 recognizable tools, instant). docs/vhs/mcp.json defines the filesystem entry via its global binary — install it first: npm i -g @modelcontextprotocol/server-filesystem.

Auth token (the authenticated step)

  • Always prompt for the token first. Insist on a short-lived, low-permission token from a TEST / throwaway account — never production. Apify: https://console.apify.com/settings/integrations. Tell the user to revoke it as soon as the recording is done.
  • Pass it inline, for the render only: APIFY_TOKEN=… vhs mcpc-demo.tape. The tape references $APIFY_TOKEN (never the literal), typed inside single quotes so bash expands it at run time — the value is never on screen, never in the GIF, never committed. Always verify a connect frame shows $APIFY_TOKEN, not the value.
  • connect auto-names the session: mcp.apify.com → @apify, mcp.json:filesystem → @filesystem. No @name needed.
  • No-token alternative (public, anonymous): mcpc connect "https://mcp.apify.com/?tools=search-actors,fetch-actor-details,docs".

Skills demo server (skills.tape, security.tape)

No public server serves the MCP Skills extension yet, so skills.tape records against the e2e test server (test/e2e/server/index-v2.ts, 2026-07-28, which serves the git-workflow / refunds / daily skill fixtures) under the name mcp.example.com. mcpc forces HTTPS for non-localhost hosts, so front it with TLS:

bash
WITH_SKILLS=true PORT=13456 pnpm exec tsx test/e2e/server/index-v2.ts &
echo "127.0.0.1 mcp.example.com" >> /etc/hosts
openssl req -x509 -newkey rsa:2048 -nodes -keyout key.pem -out cert.pem -days 2 \
  -subj "/CN=mcp.example.com" -addext "subjectAltName=DNS:mcp.example.com"
# then run any small HTTPS → http://127.0.0.1:13456 reverse proxy on 127.0.0.1:443
export NODE_EXTRA_CA_CERTS="$PWD/cert.pem" NO_PROXY="mcp.example.com,$NO_PROXY"
cd docs/vhs && vhs skills.tape

The connect stays hidden: its output names the test server ("e2e-test-server").

Keychain warning (headless only)

On a box with no keyring, the bearer-token connect prints [keychain] OS keychain unavailable, falling back to file-based credential storage …. It is environment-specific (won't appear on a normal desktop with a keyring) and there is no env var to suppress it — it's a logger.warn in src/lib/auth/keychain.ts gated only by keychain availability and JSON mode. A dbus-run-session + gnome-keyring-daemon wrapper does not fix it in this sandbox (raising the dbus fd limit is blocked). Options: leave it (honest), or add a targeted 2>/dev/null to just that one connect command.

Prerequisites

bash
mcpc --version            # the CLI being demoed (npm i -g @apify/mcpc, or build + pnpm link this repo)
vhs --version             # brew install vhs (needs ttyd + ffmpeg on PATH)
mcp-server-filesystem     # npm i -g @modelcontextprotocol/server-filesystem (the stdio demo server)

Headless + root: VHS drives a Chromium (go-rod auto-downloads it to ~/.cache/rod) that refuses to start without --no-sandbox. If renders fail to launch Chromium, wrap the binary once:

bash
CHROME=$(find ~/.cache/rod/browser -name chrome -type f | head -1)
mv "$CHROME" "$CHROME-real"
printf '#!/bin/sh\nexec "$(dirname "$0")/chrome-real" --no-sandbox --disable-gpu --disable-dev-shm-usage "$@"\n' > "$CHROME"
chmod +x "$CHROME"

(Run vhs once first to trigger the Chromium download.)

Render and verify

bash
cd docs/vhs
APIFY_TOKEN=…   vhs mcpc-demo.tape                                   # real-time; be patient
ffprobe -v error -show_entries format=duration -of csv=p=0 mcpc-demo.gif   # check length
ffmpeg -y -ss 12 -i mcpc-demo.gif -vframes 1 /tmp/f.png             # spot-check a frame, then Read it
cp mcpc-demo.gif ../images/mcpc-demo.gif                            # update the README hero

Check each frame class: empty state, stdio connect + session list, tools-list, JSON, remote connect (token NOT visible), tool-call result, close. Then revoke the token.

Optimize the GIF size (do this before committing)

VHS GIFs are large (the hero is ~5 MB raw). Shrink them losslessly-ish with gifsicle (kornel.ski/lossygif) — --lossy drops imperceptible inter-frame detail and cuts ~60% off a text-terminal GIF with no visible quality loss:

bash
# in place; lossy=200 ≈ 60% smaller, text stays crisp (verified by frame diff)
for f in docs/images/mcpc-demo.gif docs/vhs/*.gif; do
  [ "$f" = docs/vhs/mcpc-demo.gif ] && continue   # ignored raw hero
  gifsicle -O3 --lossy=200 -b "$f"
done

After optimizing, re-extract a colored frame (ffmpeg -ss 12 …) and eyeball it — lossy=200 is the sweet spot; going much higher smears the antialiased text. When the optimized hero lands on main, bump the README cache-buster (mcpc-demo.gif?v=N → ?v=N+1): GitHub's camo image proxy caches by full URL, so a new ?v= is what makes it re-fetch the smaller file instead of serving the old cached copy.

What's committed

  • docs/images/mcpc-demo.gif — the README hero (canonical copy).
  • docs/vhs/*.gif — the per-feature recordings are committed too, so they're easy to find and reuse. .gitignore ignores only docs/vhs/mcpc-demo.gif (the hero's raw output, since it's committed under docs/images/).
  • proxy.gif needs a token to record and isn't committed until recorded.

The tapes

TapeRecords
mcpc-demo.tapeHero basic-use flow (stdio + remote) → docs/images/mcpc-demo.gif
quickstart.tapeMinimal connect → list → call
tools.tapetools-list / tools-get / tools-call, inline JSON, stdin
scripting.tape--json piped through jq (code mode)
grep.tapeDynamic tool discovery with mcpc grep across two sessions (Apify + filesystem)
proxy.tapeMCP proxy / AI sandboxing (keeps a bearer token on purpose)
skills.tapeMCP Skills extension: skills-list / skills-get / resources-directory-read against the e2e test server served as mcp.example.com
security.tapeAuto-discovery skipping a checked-in .mcp.json entry that reads ${GITHUB_TOKEN} (fixture: security.mcp.json, copied into a mktemp -d HOME so no real configs are discovered); needs mcp.example.com for the trusted entry

All focused tapes follow the same conventions as the hero (bold $ prompt, bold-white commands, no comments, blank-line separation, mktemp home). quickstart/tools/scripting/grep are token-free (public ?tools= URL); grep also connects a local filesystem stdio server so it can search across two sessions. proxy.tape keeps a bearer token because demonstrating that you can proxy a credentialed session without leaking the token is its entire point (it's the one focused tape that needs a token to record).

Frequently asked questions

What does the Record Demo AI skill do?

Record or regenerate the mcpc demo GIFs (the README hero docs/images/mcpc-demo.gif and the focused tapes in docs/vhs/) with VHS. Use whenever asked to create, refresh, restyle, shorten, or fix a terminal demo/animation/GIF of mcpc. The tapes drive real mcpc commands; for the authenticated step this skill ALWAYS prompts for a short-lived, low-permission TEST token first (never production). Captures the VHS + mcpc gotchas learned the hard way — read it fully before editing a tape.

Why use Record Demo on TypingMind?

Because you install it once and use it with any model. Record Demo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Record Demo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/apify/mcpc/tree/main/skills/record-demo. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Record Demo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Record Demo?

As many as you like. As long as a model supports skills, you can use Record Demo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Record Demo AI skill free?

Yes. It is published on GitHub by apify under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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