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maginary-mcp
Advanced tools
Model Context Protocol server for Maginary — enumerate flags, kick off generations, poll results.
Model Context Protocol server for Maginary — an abstracted OpenRouter for images and video: ~20 model families (GPT-image-2, Seedance 2, Sora 2, Nano Banana Pro, Flux…) behind one Midjourney-style --flag prompt. 16 tools: full flag catalog, generate / upscale / vary / animate, in-chat signup, billing, and x402 pay-per-use for agents with a wallet.
Maginary uses a Midjourney-style --flag prompt DSL over an async HTTP API. This server:
generate tool that hits POST /api/gens/get_generation + wait_for_generation for polling to a terminal stateThis is an MCP server — you don't run it directly; your AI client (Claude Desktop, Cursor, etc.) launches and talks to it behind the scenes. Just add one config block and start chatting.
In Claude Desktop: settings → developer → edit config. That opens claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\). Add:
{
"mcpServers": {
"maginary": {
"command": "uvx",
"args": ["--upgrade", "maginary-mcp"]
}
}
}
Restart Claude Desktop. Ask it to generate an image — it will see Maginary's tools automatically.
No account yet? No problem — Claude will walk you through signup (just give it your email). Already have an API key? Add it to skip that step:
"env": { "MAGINARY_API_KEY": "sk-mag-…" }
Requires Python 3.10+ and uv. Alternatively: pip install maginary-mcp.
Nothing is required. For the stdio server you'll at most set one variable:
| var | default | meaning |
|---|---|---|
MAGINARY_API_KEY | — | Bearer token from app.maginary.ai/dashboard#api-keys. Skips the in-chat signup flow. Catalog tools work without it. |
MAGINARY_BASE_URL | https://app.maginary.ai/api | Override for staging or self-hosted. |
MAGINARY_MCP_LOG_LEVEL | INFO | Standard Python log level; goes to stderr (stdout is reserved for MCP JSON-RPC). |
The rest only apply when you run the hosted server yourself (maginary-mcp-http, see below). Directory pages that scan the code list them too; ignore them for local use.
| var (hosted only) | default | meaning |
|---|---|---|
MAGINARY_MCP_HOST / MAGINARY_MCP_PORT | 0.0.0.0 / 8642 | Bind address of the HTTP server. |
MAGINARY_PUBLIC_HOST | app.maginary.ai | Sent to the backend as X-Forwarded-Host (with -Proto/-For) when MAGINARY_BASE_URL is an internal address, so the backend builds public URLs. |
MAGINARY_MCP_REQUIRE_AUTH | off | On: every /mcp call needs a Bearer (OAuth token or API key); without one the server answers 401 + WWW-Authenticate pointing at /.well-known/oauth-protected-resource, which is how Claude/ChatGPT start the login. Trade-off: a wallet-only agent has no Bearer to send, so with the gate on it must make its first x402 payment over plain HTTP (POST /api/gens/) and then connect with a key from POST /api/auth/wallet-account/; the 401 body says so. |
MAGINARY_OAUTH_ISSUER | https://app.maginary.ai/o | The authorization server named in the protected-resource metadata (the backend, django-oauth-toolkit). |
MAGINARY_MCP_RESOURCE_URL | https://mcp.maginary.ai/mcp | This server's canonical resource identifier (RFC 8707 audience). Also what /.well-known/mcp/server-card.json advertises. |
Connect a client straight to the hosted server at https://mcp.maginary.ai/mcp.
Zero install — the server is multi-tenant, so each request is scoped to
whatever credential it arrives with. Two ways to authenticate, pick whichever
fits the client:
Connect (OAuth) — for Claude Desktop, claude.ai, and any other client that speaks MCP's OAuth spec. Add the server with no headers at all:
{
"mcpServers": {
"maginary": { "url": "https://mcp.maginary.ai/mcp" }
}
}
Click "Connect" in the client. It opens a login page on app.maginary.ai,
you sign in and approve the requested scopes, and the client holds the token
from then on — no key to generate or paste. Requires the server to be running
with MAGINARY_MCP_REQUIRE_AUTH=1; without it, no login is asked for at all.
API key — for any client that doesn't do the OAuth dance (or if you'd rather not click through a login), generate a key at app.maginary.ai/dashboard#api-keys and send it yourself:
{
"mcpServers": {
"maginary": {
"url": "https://mcp.maginary.ai/mcp",
"headers": { "Authorization": "Bearer sk-mag-…" }
}
}
}
Both are equivalent once connected — same tools, same account. Catalog tools
work with no credential either way; generate / get_generation /
wait_for_generation need one. Run the hosted server yourself with:
No key at all? Call generate anyway. Out of credits (or no account), the
result is isError: true with the x402 PaymentRequired at the top level
(accepts, resource, …) plus error: "payment_required". An x402-capable
MCP client — the x402 SDK's x402MCPSession — signs accepts[0] and calls
the same tool again with the payment in _meta["x402/payment"]. The server
forwards it to the backend as PAYMENT-SIGNATURE; the backend verifies,
settles on Base and, for a wallet with no account, creates one. The settled
result carries the on-chain receipt in _meta["x402/payment-response"] and
x402_receipt. No API key is returned — subsequent requests use wallet-signed
auth headers (X-Wallet-Address, X-Wallet-Signature, X-Wallet-Timestamp)
instead.
The server holds no payment logic; everything is decided by the backend's
/api/gens/ contract.
After the first x402 payment creates the wallet's account, all subsequent requests are authenticated by signing a short message with the wallet's private key. Three headers on every request:
| Header | Value |
|---|---|
X-Wallet-Address | Lowercased 0x EVM address (42 chars) |
X-Wallet-Signature | EIP-191 personal_sign hex over the challenge string |
X-Wallet-Timestamp | Unix seconds (integer) |
The challenge string is:
Maginary: authenticate <address> at <timestamp>. This does not move funds.
with <address> lowercased and <timestamp> the same unix seconds sent in
the header. The timestamp must be within 5 minutes of the server's clock
(30 s of future skew tolerated). No API key management needed — the wallet
is the credential.
pip install "maginary-mcp[http]"
maginary-mcp-http # serves /mcp on 0.0.0.0:8642 (MAGINARY_MCP_PORT to change)
# — or —
docker build -t maginary-mcp . && docker run -p 8642:8642 maginary-mcp
The hosted server sets no MAGINARY_API_KEY (keys come per-request). It also
serves /health, a human page at GET /, the OAuth protected-resource metadata
and an MCP server card at /.well-known/mcp/server-card.json (live tool list,
auth posture) for directories that scan a bare URL.
The server ships an Agent Skill that
teaches the --flag DSL, model selection, and the async generate→poll flow:
maginary-mcp --install-skill # -> ~/.claude/skills/maginary-image-gen/SKILL.md
The skill stands on its own — hosts without MCP get the DSL plus the raw REST
calls (POST /gens/ → poll). With the server connected, Claude instead calls
search_parameters for the authoritative flag list and generate/wait_for_generation
natively. Re-running updates it; local edits are protected unless you pass --force.
Source: src/maginary_mcp/SKILL.md.
list_parameters(category?, status?, include_reserved=false) — enumerate the catalogsearch_parameters(query, category?, include_reserved=false) — text search over names / aliases / desc / examplesget_parameter(name) — full record for one flag (canonical name or alias)list_parameters responses include the categories / statuses taxonomy, and both
list/search responses carry source (live vs bundled-snapshot).
generate(prompt, callback_url?) — POST /api/gens/. Supports img2img: place image URLs in the prompt. Multiple URLs = multi-input compositing. Use --sref <url> for style-only transfer (not img2img).upload_image(file_path, filename?) — reads a local image file and uploads via POST /api/images/upload/. Returns a CDN URL for use in img2img prompts or --sref. Stdio connections only (hosted: use a URL directly or the REST endpoint).execute_action(generation_uuid, action_type, parent_image_index?, prompt?, callback_url?) — POST /api/gens/{uuid}/actions/. Run a follow-up on a completed generation's image (upscale, vary, pan, zoom, img2vid, reroll).get_generation(uuid) — GET /api/gens/{uuid}/. Response includes processing_result.available_actions mapping slots to valid action types.wait_for_generation(uuid, timeout_s=45) — poll to done / failed; a timeout result means still running — call againInside an MCP-capable client, once configured:
"Search the maginary catalog for anything about aspect ratio."
The LLM calls search_parameters("aspect") and gets back the --ar entry with values, examples, and supported models.
"Now generate a cinematic portrait 16:9 with the flagship model."
The LLM calls generate("a cinematic portrait --ar 16:9 --flagship"), gets a uuid, then wait_for_generation(uuid) and reads image_urls[] out of the terminal record.
"Upscale the first image."
The LLM checks processing_result.available_actions["0"], sees "upscale_2x", calls execute_action(uuid, "upscale_2x", 0), gets a new uuid, then wait_for_generation(new_uuid).
"Edit this photo to look like a watercolor." (user provides a local image)
The LLM calls upload_image("/tmp/photo.png") → gets a CDN URL, then generate("https://cdn.maginary.ai/…/photo.webp reimagine as watercolor painting"). (stdio only — on hosted, the user provides a URL instead.)
https://maginary.ai/docs/parameters.json, 5-second timeout.src/maginary_mcp/parameters_snapshot.json used as a fallback whenever live fetch fails (no network, docs site down, etc.).python scripts/refresh_snapshot.py — deliberately not baked into the wheel build so a new snapshot always corresponds to a reviewed commit.The source field on list_parameters / search_parameters responses tells you which one is active.
cd mcp
python -m venv venv && source venv/bin/activate
pip install -e .
maginary-mcp # runs on stdio; kill with Ctrl+D
MIT.
FAQs
Model Context Protocol server for Maginary — enumerate flags, kick off generations, poll results.
We found that maginary-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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