Markup AI API

Name: Markup AI API
Brand: Markup AI API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAI/MLLanguage Modelsbearer28 EndpointsREST

For Agents

Run AI-driven style checks, generate suggestions, and produce full rewrites of source text against a configurable style guide via async workflow endpoints.

Install Jentic One Beta

Connect the Markup AI API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Markup 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://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | 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 Markup AI API.

Create and manage style guides that encode brand voice and grammar rules

Submit text to async style checks and poll workflow IDs for completion

Generate inline writing suggestions tied to specific style-guide rules

GET STARTED

Start building with Markup AI API

Explore with Jentic

View OpenAPI Document

Use for: I want to run a style check on a 2000-word blog post against our brand style guide, Generate writing suggestions for the introduction paragraph of this article, Rewrite this support email to match our customer-friendly tone style guide, Retrieve the result of style check workflow id wf_123

Not supported: Does not handle text generation from scratch, translation, or text-to-speech — use for style checks, writing suggestions, and rewrites against a configured style guide only.

Jentic publishes the only available OpenAPI specification for Markup AI API, keeping it validated and agent-ready. Markup AI provides programmatic access to AI-driven content quality tooling, including configurable style guides, automated style checks, suggestion generation, and full text rewrites. Each writing operation runs as a workflow with a polling interface, allowing long-form documents to be analysed asynchronously. The API is intended for content platforms, documentation tools, and AI agents that need to enforce brand voice or grammar rules at scale.

Use Cases

Patterns agents use Markup AI API for, with concrete tasks.

★ Editorial Quality Gate

Content teams running marketing or documentation pipelines need an automated quality gate before publishing. Markup AI accepts the source text, runs it against a configured style guide, and returns a workflow ID that the publishing system polls until results are ready. Typical articles complete in 5-30 seconds depending on length.

Submit a 1500-word article to `POST /v1/style/checks` with style_guide_id 'sg_brand_voice', then poll `GET /v1/style/checks/{workflow_id}` until status is complete.

AI-Assisted Rewrites in CMS

A CMS plugin can offer one-click 'rewrite to brand voice' on a draft. Markup AI's rewrites endpoint takes the draft plus a style guide ID and returns a full rewritten version. The async workflow model handles long documents without keeping HTTP connections open. Editors review the diff before publishing.

Call `POST /v1/style/rewrites` with the draft body and style_guide_id, then fetch the rewritten text from `GET /v1/style/rewrites/{workflow_id}`.

Inline Style Suggestions

Authoring tools and email clients can surface inline suggestions as the user types. Markup AI's suggestions endpoint returns rule-tagged change recommendations (e.g., 'shorten this sentence', 'use active voice') so the UI can present accept/reject affordances with rationale.

Submit a paragraph to `POST /v1/style/suggestions` with the user's style guide and return the per-sentence suggestions list.

AI Agent Content Polish

An AI agent that drafts customer emails or knowledge base articles can use Jentic to call Markup AI as a final polish step. Jentic stores the bearer token securely and exposes the style-check, suggestion, and rewrite operations through intent search, so the agent picks the right one without hard-coding endpoint paths.

Search Jentic for 'rewrite content to brand voice', load the Markup AI rewrite schema, and execute it on the draft email before sending.

Key Endpoints

28 endpoints — jentic publishes the only available openapi specification for markup ai api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/v1/style-guides

List configured style guides

GET

/v1/style-guides/{style_guide_id}

Fetch a specific style guide

POST

/v1/style/checks

Submit text for an async style check

GET

/v1/style/checks/{workflow_id}

Poll a style-check workflow result

POST

/v1/style/suggestions

Generate inline writing suggestions

POST

/v1/style/rewrites

Request a full text rewrite

GET

/v1/style/rewrites/{workflow_id}

Retrieve rewrite workflow output

GET

/v1/style-guides

List configured style guides

GET

/v1/style-guides/{style_guide_id}

Fetch a specific style guide

POST

/v1/style/checks

Submit text for an async style check

GET

/v1/style/checks/{workflow_id}

Poll a style-check workflow result

POST

/v1/style/suggestions

Generate inline writing suggestions

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Markup AI bearer tokens are stored encrypted in the Jentic vault (MAXsystem). Agents receive scoped session references and the `Authorization: Bearer ...` header is added at execution time — raw tokens never enter the agent's context.

Intent-based discovery

Agents search by intent (e.g., 'rewrite content to brand voice' or 'check writing against style guide') and Jentic returns the matching Markup AI operation with its input schema.

Time to first call

Direct Markup AI integration: 1 day for auth, async workflow polling, and error handling. Through Jentic: under 30 minutes — search, load schema, execute.

FAQs

Specific to using Markup AI API through Jentic.

Why is there no official OpenAPI spec for Markup AI API?

Markup AI does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call the Markup AI API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Markup AI API use?

Markup AI uses HTTP bearer-token authentication. Through Jentic, the bearer token is stored encrypted in the MAXsystem vault and the `Authorization: Bearer ...` header is set automatically at execution time.

Can I check content against a custom style guide with the Markup AI API?

Yes. Create a style guide via the `/v1/style-guides` endpoints, then pass its ID to `POST /v1/style/checks` along with the source text. The check runs asynchronously and the result is fetched from `/v1/style/checks/{workflow_id}`.

What are the rate limits for the Markup AI API?

Markup AI does not publish hard rate limits in the spec. Style operations are async workflows so concurrency is naturally bounded — treat 5-10 concurrent in-flight workflows per account as a safe default and back off on 429 responses.

How do I rewrite a document to match a style guide through Jentic?

Run `pip install jentic`, then use Jentic's search with the query 'rewrite content to brand voice'. Jentic loads the `/v1/style/rewrites` schema and your agent executes it with the document and style_guide_id, then polls `/v1/style/rewrites/{workflow_id}` for the result.

Are checks, suggestions, and rewrites synchronous or asynchronous?

All three follow the async workflow pattern: the POST returns a workflow_id, and the matching `GET /{workflow_id}` endpoint is polled until the workflow completes. This lets long documents finish without HTTP timeouts.

Markup AI API

Connect the Markup AI API to your agent

Capabilities

Start building with Markup AI API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs