Hand-drawn explainer illustrations in your AI host, via an MCP App with an interactive viewer.
Hand-drawn explainer illustrations in your AI host, via an MCP App with an interactive viewer. Exposed over MCP by the doodleworks mcp mcp server, that capability becomes something an assistant can invoke while it works, not something you go and do afterwards.
Bring your own image-API key (OpenAI or Gemini) · local stdio server · flip through, regenerate, and download, all in your host's chat.
Everything the assistant can do here goes through one of these:
OPENAI_API_KEY — OpenAI GPT Image (the default provider)Browse — ** step through with prev/next or the thumbnail strip; the optional 21:9 hero leads, the 16:9 tips followZoom — ** click any illustration to enlarge itRegenerate — ** image models are non-deterministic, so one click re-rolls a single illustration in place (no need to redo the whole set)Download — ** save one PNG or the whole set; tick Title on PNG to burn the title into a clean caption band below the artworkHost — Runs the toolsWindsurf — ✅illustrations — (required)title — noneresolution — 1kquality — DOODLEWORKS_QUALITY env, else lowstyleReference — DOODLEWORKS_STYLE_REF env, else noneYou will need 3 environment variables: OPENAI_API_KEY, GEMINI_API_KEY, GOOGLE_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Installation goes through your MCP client rather than a global install: point it at doodleworks-mcp on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Doodleworks MCP's toolset — OPENAI_API_KEY, Browse, Zoom and 11 more — is a fair guide to whether it matches your workflow. It is maintained by SalZaki; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Doodleworks MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| OPENAI_API_KEY | OpenAI GPT Image *(the default provider)* |
| Browse | ** step through with prev/next or the thumbnail strip; the optional 21:9 hero leads, the 16:9 tips follow. |
| Zoom | ** click any illustration to enlarge it. |
| Regenerate | ** image models are non-deterministic, so one click re-rolls a single illustration in place (no need to redo the whole set). |
| Download | ** save one PNG or the whole set; tick **Title on PNG** to burn the title into a clean caption band below the artwork. |
| Host | Runs the tools |
| Windsurf | ✅ |
| illustrations | *(required)* |
| title | none |
| resolution | 1k |
| quality | DOODLEWORKS_QUALITY env, else low |
| styleReference | DOODLEWORKS_STYLE_REF env, else none |
| prompt | *(required)* |
| aspect | 16:9 |
{
"mcpServers": {
"doodleworks-mcp": {
"command": "npx",
"args": ["-y", "doodleworks-mcp"],
"env": { "OPENAI_API_KEY": "sk-..." }
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| OPENAI_API_KEY | Credential the server authenticates with. | Yes |
| GEMINI_API_KEY | Credential the server authenticates with. | Yes |
| GOOGLE_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.