Install Jentic One Beta

Connect the AuditAE REST API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AuditAE REST 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%2Fauditae.app%2Fauditae" | 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%2Fauditae.app%2Fauditae" | 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 AuditAE REST API.

Check whether AI answer engines like ChatGPT, Perplexity, and Gemini cite a brand for a given prompt

Run a broader answer-engine audit and fetch its result by id

Crawl a site and check a single page's technical setup

Generate schema.org JSON-LD and validate existing JSON-LD markup

Discover a brand's entity on Wikidata and read the workspace balance and prices

GET STARTED

Start building with AuditAE REST API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use AuditAE REST API for, with concrete tasks.

★ Answer-Engine Citation Monitoring

See whether AI answer engines mention a brand before competitors notice. An agent sends a prompt to the check operation, reads which of ChatGPT, Perplexity, Gemini, and Google AI Overviews cite the brand, and runs a wider audit to track coverage over time. The result is a concrete citation map an agent can report against.

Run a check for a prompt, then start an audit and poll its result by id

Schema and Technical Readiness

Make a site easier for AI answer engines to read. An agent crawls the site, checks one page's technical setup, then generates schema.org JSON-LD and validates existing markup. This closes the structured-data gaps that keep a page from being cited.

Crawl a site, generate JSON-LD for a page, then validate the resulting markup

AI Agent Integration via Jentic

An AI agent discovers and calls AuditAE through Jentic without handling the ae_live key directly. The agent searches by intent, receives the matching operation and its input schema, and runs the check or audit while Jentic injects the stored key. Paid calls draw from the prepaid balance the agent can read first.

Search Jentic for 'check answer-engine citations', load the operation schema, and run the check with Jentic-injected credentials

Key Endpoints

10 endpoints — the auditae rest api checks whether ai answer engines such as chatgpt, perplexity, gemini, and google ai overviews cite a brand, and audits the technical signals that make a site answer-ready.

METHOD

PATH

DESCRIPTION

POST

/api/v1/check

Check one prompt across answer engines

POST

/api/v1/audits

Run an audit

GET

/api/v1/audits/{id}

Get an audit result by id

POST

/api/v1/crawl

Crawl a site

POST

/api/v1/schema/generate

Generate schema.org JSON-LD

POST

/api/v1/entities/discover

Find a brand on Wikidata

POST

/api/v1/check

Check one prompt across answer engines

POST

/api/v1/audits

Run an audit

GET

/api/v1/audits/{id}

Get an audit result by id

POST

/api/v1/crawl

Crawl a site

POST

/api/v1/schema/generate

Generate schema.org JSON-LD

POST

/api/v1/entities/discover

Find a brand on Wikidata

Why Jentic?

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

Setup

Wiring AuditAE by hand means creating an ae_live_ key, sending it as a Bearer token on auditae.app, and tracking your prepaid balance so paid calls do not fail with a top-up request. Through Jentic you install once, import AuditAE from the API Directory, store the key once, and your agent calls it.

Permission scoping

Through Jentic you limit the agent to the operations it needs, such as running citation checks and audits, while leaving the billing top-up operation out of the set so it cannot spend your prepaid balance.

Credential isolation

Your AuditAE key 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 'check answer-engine citations' or 'generate schema JSON-LD', and Jentic returns the matching AuditAE operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using AuditAE REST API through Jentic.

What authentication does the AuditAE REST API use?

The AuditAE REST API authenticates with an ae_live_ key sent as a Bearer token in the Authorization header, per its OpenAPI spec. The same key draws paid calls from your prepaid workspace balance. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never reaches the agent.

Is there an AuditAE MCP server?

You do not need a separate MCP server to give your agent AuditAE. Jentic connects it directly from the API Directory: import AuditAE, store your key once, and your agent calls its check, audit, and schema operations on demand. Operations are discovered as needed, so no extra server's tool definitions load into the agent's context.

Can I check whether ChatGPT cites my brand with the AuditAE REST API?

Yes. Send the prompt to the check operation and the API returns which answer engines, including ChatGPT, Perplexity, and Gemini, cite the brand. Run the audit operation for a broader sweep and fetch its result by id.

Can I limit what my agent is allowed to do with the AuditAE REST API?

Yes. Because you run Jentic One yourself, your rules decide which AuditAE operations the agent may call. You can allow the citation checks and audits while withholding the billing top-up operation so the agent cannot spend your prepaid balance, and every call is logged.

What are the rate limits for the AuditAE REST API?

The OpenAPI spec does not specify request rate limits; instead, paid calls draw from a prepaid balance and free calls do not. Read the balance and prices on the billing operation, or see the AuditAE documentation at https://auditae.app for current terms.

How do I check answer-engine citations with the AuditAE REST API through Jentic?

Search Jentic for 'check answer-engine citations' to get the matching AuditAE operation and its input schema, then your agent runs the check and parses which engines cite the brand. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Auditae App AuditAE REST API

AI ReadinessAI-Aware (B+)67/100

See full scorecard

Official vendor OpenAPI document · agent-readyMarketingSeo Sembearer10 EndpointsREST

For Agents

Check whether AI answer engines cite a brand, crawl and audit pages, and generate or validate schema.org JSON-LD, across 10 endpoints secured with a bearer API key.

Use for: Check whether ChatGPT cites my brand for a prompt, I need to run an answer-engine audit for a domain, Get the result of an audit by its id, Generate schema.org JSON-LD for a page

Not supported: Does not run paid search ads, manage backlinks, or track keyword rankings. Use for auditing AI answer-engine citations and schema.org structured data only.

The AuditAE REST API checks whether AI answer engines such as ChatGPT, Perplexity, Gemini, and Google AI Overviews cite a brand, and audits the technical signals that make a site answer-ready. It runs a single prompt across engines, runs a broader audit and returns its result by id, crawls a site, and checks one page's technical setup. It also generates and validates schema.org JSON-LD and discovers a brand's entity on Wikidata. Paid calls draw from a prepaid workspace balance, which the billing operations report and top up.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

98%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

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

75%

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: B+Signals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

75%

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: DSignals: 4

38%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

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

48%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

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: ASignals: 1

81%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the AuditAE REST API to your agent

Capabilities

Start building with AuditAE REST API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Auditae App AuditAE REST API

Jentic AI Readiness Score

AuditAE REST 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