Install Jentic One Beta

Connect the Leonardo.Ai API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Leonardo.Ai API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fleonardo.ai%2Fleonardo" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fleonardo.ai%2Fleonardo" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Leonardo.Ai API.

Create image generations from a text prompt and poll for the results

Retrieve a generation and its resulting images by ID

Create datasets and upload images for model training

Train a custom model on your own dataset

Run upscale, unzoom, and background-removal variations on an image

GET STARTED

Start building with Leonardo.Ai API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Leonardo.Ai API for, with concrete tasks.

★ AI Creative Agent via Jentic

An AI creative agent can generate and refine images without a developer wiring the Leonardo.Ai API by hand. Through Jentic the agent searches for the generation operation by intent, receives the endpoint and its input schema, and calls it with the bearer token injected at execution time. The agent then polls the generation by ID and returns the finished images.

Search Jentic for 'create an image generation', call POST /generations with the prompt, then poll GET /generations/{id} until the images are ready

Custom Model Training

Teams with their own image style can train a custom model rather than relying on base models. The Leonardo.Ai API builds a dataset, uploads training images, and trains a model against it, so a pipeline can produce a bespoke model programmatically. The trained model is then available for later generations.

Call POST /datasets to create a dataset, upload images to it, then POST /models to train a custom model on the dataset

Image Post-Processing

Applications that generate images often need to upscale or clean them up before delivery. The Leonardo.Ai API runs upscale, unzoom, and background-removal variations on an existing image, so a post-processing step can polish each result. This produces delivery-ready assets without leaving the platform.

Call POST /variations/upscale on a generated image, then retrieve the variation result by ID

Key Endpoints

55 endpoints — the leonardo.

METHOD

PATH

DESCRIPTION

POST

/generations

Create a generation of images

GET

/generations/{id}

Get a single generation

POST

/datasets

Create a dataset

POST

/models

Train a custom model

POST

/variations/upscale

Create an upscale variation

POST

/prompt/improve

Improve a prompt

POST

/generations-text-to-video

Create a video generation from a text prompt

GET

/me

Get user information

POST

/generations

Create a generation of images

GET

/generations/{id}

Get a single generation

POST

/datasets

Create a dataset

POST

/models

Train a custom model

POST

/variations/upscale

Create an upscale variation

POST

/prompt/improve

Improve a prompt

POST

/generations-text-to-video

Create a video generation from a text prompt

GET

/me

Get user information

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the Leonardo.Ai API by hand means setting the bearer token on every request, starting a generation, and polling its ID until the images are ready yourself. Through Jentic you install once, import Leonardo.Ai from the API Directory, store the token once, and your agent calls it.

Permission scoping

Leonardo.Ai puts the record id in the URL path (/generations/{id}, /datasets/{id}), so a rule can pin your agent to creating and reading generations. You choose the operations it may call, so training a model or deleting a dataset is not included unless you add it.

Credential isolation

Your Leonardo.Ai token is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'create an image generation' or 'train a custom model', and Jentic returns the matching Leonardo.Ai operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using Leonardo.Ai API through Jentic.

What authentication does the Leonardo.Ai API use?

The Leonardo.Ai API authenticates with a bearer token in the Authorization header, as declared in its OpenAPI spec. Through Jentic the token is stored encrypted by your own Jentic One instance and injected at execution time, so it never enters the agent's prompt, logs, or context.

How do I get the images from a generation with the Leonardo.Ai API?

Call POST /generations to start a generation, which returns a generation ID, then poll GET /generations/{id} until the images are ready. The generation response carries the URLs of the finished images so your agent can download them.

What are the rate limits for the Leonardo.Ai API?

The OpenAPI spec does not specify rate limits. Check the Leonardo.Ai API documentation at https://docs.leonardo.ai for current limits before running high-volume generation jobs.

How do I generate images through Jentic?

Search Jentic for 'create an image generation', which resolves to the POST /generations operation, and Jentic returns its input schema so your agent can submit a prompt and poll for results. Credentials are injected at call time from your own instance. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Can I restrict what my agent is allowed to do with the Leonardo.Ai API?

Yes. Write a rule that allows only the operations your agent needs, such as POST /generations and GET /generations/{id}, so it can create and read generations but cannot train models or delete datasets, and every call it makes is logged by your own instance. You add training or delete operations to the allowed set only when you decide to.

Is there a Leonardo.Ai MCP server?

You don't need an MCP server to give your agent Leonardo.Ai. Jentic connects it directly from the API Directory: import Leonardo.Ai, store your token once, and your agent calls the generation, dataset, and model operations on demand without loading another server's tool definitions into its context.

Leonardo.Ai API

AI ReadinessAI-Aware (B-)61/100

See full scorecard

Official vendor OpenAPI document · agent-readyAI/MLVisionbearer55 EndpointsREST

For Agents

Generate images and video from prompts, train custom models on your datasets, and run upscales and variations with the Leonardo.Ai API. Covers 55 endpoints across generations, datasets, models, and variations.

Use for: Generate a set of images from a text prompt, Check the status and results of a specific generation, Train a custom model on a dataset of my images, Upscale a generated image to a higher resolution

Not supported: Does not host or serve the generated assets long term. Use for creating generations, training models, and running image variations only.

The Leonardo.Ai API generates images and video from text prompts and trains custom image models, exposing generations, datasets, models, and variations over a REST interface. It lets you start a generation, poll for its results, build datasets, train a custom model, and run upscales and other variations on an image. Requests carry a bearer token and return structured JSON your application can act on.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: CSignals: 4

92%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

21%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: CSignals: 4

Example Density

How richly the API is illustrated with examples.

83%

Example Validity

Percentage of examples that conform to their schemas.

25%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: CSignals: 4

56%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

98%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

60%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

93%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: B-Signals: 1

60%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: B+Signals: 1

67%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Leonardo.Ai API to your agent

Capabilities

Start building with Leonardo.Ai API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Leonardo.Ai API

Jentic AI Readiness Score

Leonardo.Ai API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness