Bring Generative Ai
to Cline
Learn how to connect Leonardo.ai (Generative AI & Models) to Cline and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for Subscribers
What is the Leonardo.ai (Generative AI & Models) MCP Server?
Connect your Leonardo.ai account to any AI agent and take full control of state-of-the-art generative image production and custom AI models through natural conversation.
What you can do
- Generation Orchestration — Initiate asynchronous image generation requests defining precise prompts, model UUIDs, and dimensions directly from your agent
- Model Discovery — Enumerate global platform models (Phoenix, Kino XL) and your fine-tuned custom models to understand available inference capabilities
- Image-to-Image — Acquire secure presigned URLs to upload initial images for guided AI generation and reference-based transformations
- Precision Variations — Create unzoom context extensions and visual variations expanding previously generated images while maintaining structural consistency
- Inventory Audit — List recent user generations and retrieve absolute image URLs, prompts used, and exact hardware metadata securely
- User Metrics — Monitor active account metrics and token usage allocations to manage your generation budget and operational costs in real-time
How it works
1. Subscribe to this server
2. Enter your Leonardo.ai API Key
3. Start generating professional AI visuals from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Digital Artists & Designers — iterate on visual concepts and model fine-tuning through natural conversation without manual dashboard searching
- AI Content Teams — automate the production of high-fidelity marketing assets and branded imagery across multiple projects
- Creative Directors — audit generation histories and monitor team credit usage to ensure optimized AI resource allocation
Built-in capabilities (10)
Create an unzoom context extension expanding a Leonardo.ai generated image
Delete a Leonardo generation history log and its image array explicitly
Returns a Generation ID used to poll for the output. Generate images from a text prompt using Leonardo.ai
Get the active status or completed result of a generation
Get specific details and parameters of a Leonardo.ai model
Get active authenticated Leonardo AI user metrics
List fine-tuned and custom-trained models available explicitly on your Leonardo instance
List all global public platform models hosted on Leonardo.ai
List recent image generations initiated by a specific Leonardo user
Acquire a secure presigned URL tracking for image-to-image inference datasets
Why Cline?
Cline operates autonomously inside VS Code. it reads your codebase, plans a strategy, and executes multi-step tasks including Leonardo.ai (Generative AI & Models) tool calls without waiting for prompts between steps. Connect 10 tools through Vinkius and Cline can fetch data, generate code, and commit changes in a single autonomous run.
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Cline operates autonomously. it reads your codebase, plans a strategy, and executes multi-step tasks including MCP tool calls without step-by-step prompts
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Runs inside VS Code, so you get MCP tool access alongside your existing extensions, terminal, and version control in a single window
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Cline can create, edit, and delete files based on MCP tool responses, enabling end-to-end automation from data retrieval to code generation
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Transparent execution: every tool call and file change is shown in Cline's activity log for full visibility and approval before committing
Leonardo.ai (Generative AI & Models) in Cline
Leonardo.ai (Generative AI & Models) and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Leonardo.ai (Generative AI & Models) to Cline through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Leonardo.ai (Generative AI & Models) in Cline
The Leonardo.ai (Generative AI & Models) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Cline only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Leonardo.ai (Generative AI & Models) for Cline
Every tool call from Cline to the Leonardo.ai (Generative AI & Models) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check the progress of my image generation through my agent?
Yes. Use the get_generation_status tool with the Generation ID provided when you started the request. Your agent will poll the Leonardo API and return the final image URLs and metadata once the process is complete.
How do I find which AI models are available for generation?
Ask your agent to list_platform_models or list_custom_models. It will return a list of available UUIDs and model names (like Phoenix or Kino XL), which are required when triggering a new image generation request.
Can my agent perform image-to-image transformations?
Absolutely. Use the upload_init_image tool to acquire a secure presigned URL for your source image. Once uploaded, you can command your agent to trigger a generation that uses that image as a reference for guided AI transformations.
How does Cline connect to MCP servers?
Cline reads MCP server configurations from its settings panel in VS Code. Add the server URL and Cline discovers all available tools on initialization.
Can Cline run MCP tools without approval?
By default, Cline asks for confirmation before executing tool calls. You can configure auto-approval rules for trusted servers in the settings.
Does Cline support multiple MCP servers at once?
Yes. Configure as many servers as needed. Cline can use tools from different servers within the same autonomous task execution.
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