Skip to main content
Glama
rocnubie

Tiramisu AI MCP Server

by rocnubie
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
JavaScript
Local

Tiramisu AI MCP Server

MCP server for Tiramisu AI

MCP Badge License: MIT Zero Config Node Stdio Transport Read Only MCP

A Model Context Protocol server that exposes the canonical Tiramisu AI knowledge surface — official site information, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://tiramisuai.com

✨ About Tiramisu AI

Tiramisu AI is a web-based creative platform that brings together text-to-video generation, image-to-video conversion, image creation, and photo editing tools under a single interface. Rather than routing work across multiple specialized services, users can describe a scene in plain text and receive a video clip, animate a still photograph, generate original images from prompts, or swap backgrounds — all without leaving the platform. The service offers a free tier with daily credits and no watermarks, making it accessible for experimentation before committing to a paid plan. Both casual creators and professional teams will find the workflow familiar: upload or describe, choose a model, generate, and export.

Related MCP server: Producer AI MCP Server

Key Features

  • Multi-model video generation: Access to a curated set of video models — including Kling, Veo 3, Minimax Hailuo, Pixverse, Seedance, Wan 2.5, and others — selectable from a single dashboard without separate accounts or API keys per provider.

  • Text-to-video and image-to-video: Generate short video clips from written descriptions or animate existing photos with realistic motion, with output lengths ranging from a few seconds on the free tier up to 20 seconds on premium plans.

  • Image generation and editing: Over 15 image models available for creating visuals from prompts, alongside practical editing tools for background removal, background replacement, and face swapping.

  • Export quality tiers: Free accounts receive 720p MP4 exports; premium plans add 1080p and 4K options along with batch processing for higher-volume workflows.

  • API access: Developers can integrate generation capabilities into their own applications through an API, removing the need to build model infrastructure from scratch.

  • No-watermark free tier: Daily free credits produce clean outputs, which is less common among comparable platforms that restrict watermark removal to paid subscribers.

Use Cases

  • Social media content production: Create short-form video clips for Instagram Reels, TikTok, or YouTube Shorts directly from text descriptions or product photos, without video editing software.

  • E-commerce product visualization: Animate catalog images to show products in motion, or generate lifestyle imagery around static product shots to enrich listings and ads.

  • Marketing asset creation: Produce video drafts and image variations for campaigns without waiting on external creative vendors, then refine in-platform before handoff.

  • Prototype and concept demos: Developers and product teams can generate quick visual mockups or animated concept clips to communicate ideas before committing to full production.

  • API-driven content pipelines: Integrate Tiramisu AI's generation endpoints into automated workflows — for example, dynamically producing video summaries or image assets at scale for a content-heavy application.

Who Is It For

Tiramisu AI suits a broad range of users who need AI-generated visual content without managing separate model subscriptions or building their own generation stack. Content creators working across YouTube, TikTok, or Instagram will find the free tier practical for regular output. Marketing managers and social media teams benefit from the ability to produce and iterate on assets quickly inside one tool. E-commerce operators can use image-to-video features to make product pages more engaging. Developers who want to add video or image generation to their own products can access the same models through the API rather than negotiating individual provider agreements. The platform scales from individual hobbyist use up to team-level batch workflows.

Tools

get_site_overview

Return the canonical site overview so an agent has authoritative product context. (Tiramisu AI)

Input: no parameters. Returns: text/markdown.

get_pricing

Return the canonical pricing entry point for Tiramisu AI.

Input: no parameters. Returns: text/markdown.

get_official_links

Return the canonical list of official links for Tiramisu AI (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://tiramisu-ai/overview — Public site overview.

  • site://tiramisu-ai/pricing — Canonical pricing entry point.

  • site://tiramisu-ai/faq — Short FAQ generated from public site metadata.

  • site://tiramisu-ai/links — Canonical URLs to share with users.

Prompts

tell_me_about_tiramisu_ai

Summarize what the site is, who it's for, and how it works. — Tiramisu AI

walk_me_through_tiramisu_ai

Tour the official site with citations. — Tiramisu AI

Installation

Install via Smithery

npx -y @smithery/cli install tiramisu-ai-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

git clone https://github.com/rocnubie/tiramisu-ai-mcp.git
cd tiramisu-ai-mcp
pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{
  "mcpServers": {
    "tiramisu-ai-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/tiramisu-ai-mcp/src/index.mjs"
      ]
    }
  }
}

Debug with MCP Inspector

npx @modelcontextprotocol/inspector node src/index.mjs

Official Links

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

Available Tools

3 tools
get_pricingA

Return the canonical pricing entry point for Tiramisu AI.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the burden of conveying behavioral traits. It indicates a read-only operation via 'Return', but does not disclose what exactly is returned (e.g., URL, object), or whether any authentication or rate limits apply. It is minimally adequate but lacks depth beyond the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that states the tool's purpose without any fluff. It is appropriately sized for a tool with no parameters and effectively conveys the core functionality in a front-loaded manner.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (no parameters, no output schema), but the description is somewhat ambiguous: 'canonical pricing entry point' could mean a URL, a set of pricing details, or an internal identifier. Without an output schema or further explanation, the agent may not know what to expect from the return value, leaving a notable gap in completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics, and the empty schema leaves nothing to clarify. The description adds no parameter information, but none is required.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool returns the canonical pricing entry point for Tiramisu AI, using a specific verb ('Return') and a clear resource ('pricing entry point'). This clearly differentiates it from sibling tools like get_site_overview and get_official_links, which handle other aspects of the site.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternative tools, nor does it mention any exclusions or prerequisites. The intended use case must be inferred entirely from the tool's name and purpose, leaving the agent without explicit selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_site_overviewA

Return the canonical site overview so an agent has authoritative product context. (Tiramisu AI)

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description carries the full burden of behavioral disclosure. The terms 'canonical' and 'authoritative' add meaningful context that the tool returns a definitive, unfiltered view, which is valuable. It does not discuss potential limitations (e.g., caching, data format), but for a parameterless read operation this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that states the action, the resource, and the rationale. It contains no wasteful filler, and the parenthetical 'Tiramisu AI' is minor and does not detract from clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless, straightforward retrieval tool, the description provides sufficient context about what is returned and why. There is no output schema, but the description's explicit mention of 'canonical site overview' and 'authoritative product context' makes the tool's role clear and complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema already provides full coverage (empty properties). The description doesn't need to explain parameters, and the baseline score for 0 params is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Return' and identifies the resource 'canonical site overview', making the tool's function unambiguous. This clearly distinguishes it from sibling tools like get_pricing and get_official_links, which target different data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states the purpose ('so an agent has authoritative product context'), which implies when to use this tool: whenever a definitive overview is needed. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to make a reasonable choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 3 tool updatesv0.1.0
    • First observedget_official_links
    • First observedget_pricing
    • First observedget_site_overview
Install Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a distinct purpose: site overview, pricing, and official links. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tool names follow a consistent 'get_' + resource pattern, which is predictable and uniform.

Tool Count5/5

With only 3 tools, the server is tightly scoped to its purpose of providing canonical product information. Each tool earns its place.

Completeness4/5

The set covers the core informational needs (overview, pricing, links). Minor gaps like detailed feature lists or docs could exist, but the official links may compensate.

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rocnubie/tiramisu-ai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server