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  3. Imaginode
Imaginode logo
Health: ActiveRecent health check succeeded.Last checked 10/8/2026, 12:45:50 AM

Imaginode

User RatingsBe the first to rate and review this MCP server!
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website
image-generationvideo-generationmultimediatemplatesmodel-catalogue

Generate images and videos through imaginode.ai with model discovery, templates, pricing, status tracking, and automatic refunds.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "imaginode": {
      "url": "https://imaginode.ai/api/mcp"
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (6) Directory Badge Claim listing Alternatives🎥 More in Multimedia Process

Overview

The imaginode MCP server connects MCP clients to imaginode.ai for generating AI images and videos across its model catalogue. It lists models, prices, and canvas templates, then either returns an image URL or tracks an asynchronous video job by request ID. OAuth 2.1 is available for supported clients, while API keys can authenticate scripts and clients without OAuth. Reach for it when an agent needs multimodal generation with visible credit costs and automatic refunds for failed jobs.

Use cases

•Generate images from text prompts
•Start and monitor asynchronous video jobs
•Compare model prices before generation
•Inspect canvas templates and their recipes
•Track failed jobs and automatic refunds

Key features

•Image generation with returned output URLs
•Asynchronous video generation with status polling
•Model catalogue with credit pricing
•Curated canvas template discovery
•OAuth 2.1 and API-key authentication
•Automatic refunds for failed generations

Capabilities & Tool Schemas (6) ~170 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server — may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Imaginode.

list_models

Catalogue of image and video models with prices in credits and billable options.

list_templates

The curated canvas templates: what each produces, its models, the approximate cost of one run.

get_template

Full recipe of a template (nodes, models, prompts, wiring, example renders) and the link that opens it in the canvas.

generate_image

Generates an image and waits for the result: the URL is returned directly. Default model: Nano Banana 2.

generate_video

Starts a video generation and returns a `request_id` plus the exact cost. Default model: Seedance 2.0.

get_generation_status

Follows a generation (`running`, `completed` with output URLs, or `failed` with automatic refund).

How Imaginode works

What the imaginode MCP server does

The imaginode MCP server exposes imaginode.ai’s image and video creation capabilities through MCP. It provides access to a catalogue of 89 models, including image and video options, with pricing shown in credits and billable settings. A generation uses the credits on the connected Imaginode account and cannot exceed its available balance.

The server also exposes curated canvas templates. These cover workflows such as product imagery, renovations, video effects, children’s books, and thumbnails. Agents can inspect what a template creates, which models it uses, its approximate run cost, and the canvas link for opening the recipe.

How it works

The imaginode MCP server is hosted remotely at https://imaginode.ai/api/mcp and uses Streamable HTTP, so there is no local server package to install. An MCP client connects to that endpoint and authenticates either through OAuth 2.1 or an API key. OAuth uses authorization code flow with PKCE and supports refresh tokens; API keys are created in the Imaginode profile and sent as bearer tokens.

Image generation waits for completion and returns the resulting URL. Video generation starts a job and returns a request ID together with the exact cost. The client can then call the status tool to see whether the job is still running, completed with output URLs, or failed. Video jobs usually take one to five minutes and can take up to 30 minutes for long jobs, so polling every 30 seconds is recommended.

Setup and configuration

Create an Imaginode account with a verified email address; trial credits are included. Add the remote MCP URL in a compatible client, then complete the browser sign-in when OAuth is offered. For clients or scripts that do not support OAuth, create an API key in the profile and provide it in the Authorization: Bearer header.

The repository also includes an optional Claude Code skill. Copying skills/imaginode to ~/.claude/skills/imaginode provides usage guidance focused on cost-aware iteration, choosing cheaper models first, and polling generation jobs.

Tools and capabilities

  • list_models returns image and video models, prices, and billable options.
  • list_templates describes available canvas templates, their models, outputs, and approximate costs.
  • get_template returns a template’s nodes, prompts, model choices, connections, example renders, and canvas URL.
  • generate_image creates an image and returns its URL after completion. Its default model is Nano Banana 2.
  • generate_video starts a video job and returns its request ID and exact cost. Its default model is Seedance 2.0.
  • get_generation_status reports progress, output URLs, or failure with an automatic refund.

Limitations and notes

The imaginode MCP server applies a limit of 10 generations per minute to each API key and OAuth access token. OAuth access tokens last one hour and refresh silently. API keys are shown only once, can be revoked, and are limited to five active keys per account.

Input images must already be hosted in the user’s Imaginode media library or come from earlier generations. The direct REST API exposes the same model, generation, and status operations, including a public unauthenticated model catalogue. The repository is MIT licensed; the running service is hosted by imaginode.ai.

Read the full README →View source on GitHub →

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  • MediaEngine logoMediaEngine

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
1
Stargazers on the source repository.
Last commit
26d ago
Most recent push to the default branch.
Tools exposed
6
Callable tools this server registers over MCP.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Imaginode

imaginode is an MCP server that connects AI assistants to imaginode.ai for image and video generation. Its main tools list available models and templates, inspect template recipes, generate images, start video jobs, and check generation status. It reports credit costs and refunds failed generations automatically.

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Technical Specs & Signals

Category🎥Multimedia Process
More technical detailsExpand ▾
TransportSSE (Remote)
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 6, 2026
6/6 checks healthy over the last 38d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
Last commit26d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 13, 2026
52Quality signal: Good · 52/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools25/30
Adoption & activity4/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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