Install Jentic One Beta

Connect the INITE AI Visibility to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the INITE AI Visibility, 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%2Finite.ai%2Finite" | 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%2Finite.ai%2Finite" | 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 INITE AI Visibility API.

Read the structured INITE company record, including services, prices, the service ladder, and the analyzer feature list, via /api/ai-data

Render an SVG AI visibility badge for a shared audit report, choosing a flat or gradient style and a dark or light theme

Call one tool rail at a time (portal, analyzer, or atlas) through the rail path parameter on /api/mcp/{rail}

Run the analyzer rail's identity check and AI visibility audit as a guest, or with a token for the account's own tier

GET STARTED

Start building with INITE AI Visibility API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use INITE AI Visibility API for, with concrete tasks.

★ AI visibility checks from your agent through Jentic

An AI agent connected through Jentic checks how visible a website is to AI answer engines by calling INITE's analyzer rail on the JSON-RPC endpoint. A guest call returns the audit as a survey under per-address allowances, and adding an OpenID Connect token unlocks the account's own tier. Jentic gives the agent the operation and its input schema, so it does not have to read INITE's discovery documents first.

Call POST /api/mcp/{rail} with rail 'analyzer' and a JSON-RPC 2.0 body (jsonrpc '2.0', method set to the analyzer's audit tool call, params naming the site), then report the composite score

Show an audit score on your site

After an audit, a site owner places INITE's badge on their own pages. The badge operation takes the public share id of the report in the report parameter and prints that report's composite score, with style set to flat or gradient and theme set to dark or light. The score is read from the report itself, never from the URL, and without a report the badge shows no score.

Call GET /api/badge with report 'abc123', style 'flat', and theme 'light', then return the SVG markup for embedding

Answer questions about INITE's offer

Agents that need to answer questions about what INITE sells read the company record from the public data endpoint. It returns services, prices, the service ladder, site routes, the analyzer feature list, and the FAQ, with English as the canonical language. The shape follows what INITE currently sells, so read fields rather than pinning to a fixed schema.

Call GET /api/ai-data and summarise the listed services with their prices

Agent-to-agent task handoff

Another agent can delegate work to INITE over Agent2Agent v1.0. It sends SendMessage to start a task, then uses GetTask or ListTasks to follow progress and CancelTask to stop one. Task states arrive as ProtoJSON enums such as TASK_STATE_WORKING, and only A2A-Version 1.0 is accepted.

Call POST /api/a2a with header A2A-Version '1.0' and body jsonrpc '2.0', method 'SendMessage', then poll with method 'GetTask' until the task leaves TASK_STATE_WORKING

Key Endpoints

5 endpoints — the inite ai visibility api exposes inite's ai visibility audit and the company data behind it over http.

METHOD

PATH

DESCRIPTION

GET

/api/ai-data

Get structured company data

GET

/api/badge

Get an embeddable AI visibility badge

POST

/api/mcp/{rail}

Call one tool rail over JSON-RPC

POST

/api/a2a

Send an Agent2Agent JSON-RPC request

GET

/api/ai-data

Get structured company data

GET

/api/badge

Get an embeddable AI visibility badge

POST

/api/mcp/{rail}

Call one tool rail over JSON-RPC

POST

/api/a2a

Send an Agent2Agent JSON-RPC request

Why Jentic?

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

Setup

Wiring INITE by hand means reading separate discovery documents for its JSON-RPC surfaces, handling OpenID Connect tokens with a different audience per endpoint, and pinning the A2A-Version header. Through Jentic you install once, import INITE from the API Directory, optionally store a token once, and your agent calls it.

Permission scoping

INITE puts the tool rail in the URL path of its JSON-RPC endpoint, so a rule can pin your agent to one rail such as analyzer and the operations you pick. The individual tool and the A2A method travel inside the JSON-RPC body, so within a rail rules bound which operations your agent may call, not which tool.

Credential isolation

If you add an INITE token, it 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 'run an AI visibility audit' or 'get INITE pricing', and Jentic returns the matching INITE operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using INITE AI Visibility API through Jentic.

Is there an INITE MCP server?

Yes. INITE serves its own MCP endpoint, described by the server card linked from its spec. You can also connect INITE directly through Jentic: your agent gets the full 5-endpoint surface from the spec without loading another server's tool definitions into its context, any token is injected at call time by your self-hosted instance instead of living in an MCP config, and your rules decide which operations the agent may call.

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

Yes. Write a rule that allows only POST /api/mcp/{rail} with rail set to analyzer, plus GET /api/badge. Your agent can run audits and fetch score badges, but it cannot reach the portal rail's booking and contact tools or hand tasks to the A2A endpoint, and every call it makes is logged.

What authentication does the INITE API use?

Per its OpenAPI spec, authentication is optional. GET /api/ai-data and GET /api/badge are public. The JSON-RPC endpoints accept anonymous guest calls or an OpenID Connect bearer token issued by auth.inite.ai, with a separate token audience for the MCP endpoint and for the A2A endpoint. A member tool called without a token answers 401. Through Jentic, a token is stored encrypted by your own Jentic One instance and injected only into the calls that use it.

What does each INITE tool rail cover?

Per the spec, the portal rail covers services, prices, call slots, booking, contact, and guides; the analyzer rail covers the identity check and the AI visibility audit; and the atlas rail covers tool matching, a tool's measured record, search, market changes, and coupons. POST /api/mcp/{rail} serves a single rail, and a token minted for the full endpoint is accepted there.

What are the rate limits for the INITE API?

The OpenAPI spec does not publish numeric rate limits. It says guests on the JSON-RPC endpoint get the open tools under per-address allowances, and a token applies the account's own tier; check https://inite.ai for current limits.

How do I run an AI visibility audit with the INITE API through Jentic?

Install Jentic One with `curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh` and import INITE from the API Directory. Your agent searches for 'run an AI visibility audit', gets POST /api/mcp/{rail} with its input schema, and calls it with rail analyzer and a JSON-RPC 2.0 body. To run it on your own infrastructure, install Jentic One from its GitHub repo.

INITE AI Visibility

AI ReadinessAI-Aware (B)65/100

See full scorecard

Official vendor OpenAPI document · agent-readyMarketingSeo SemopenIdConnect (optional)5 EndpointsREST

For Agents

Read INITE's structured company data, render an AI visibility score badge for a shared audit report, and call the portal, analyzer, and atlas tool rails or the Agent2Agent endpoint over JSON-RPC.

Use for: Get INITE's current services and prices, Embed the AI visibility badge for my shared audit report, Run an AI visibility audit on my website, I want to check which tools match my use case on the atlas rail

Not supported: Does not handle search engine keyword tracking, backlink analysis, or publishing website content. Use for INITE's AI visibility audit, its company data, and its agent task endpoints only.

The INITE AI Visibility API exposes INITE's AI visibility audit and the company data behind it over HTTP. Two public reads return a structured company record (services, prices, the analyzer feature list, and the FAQ) and an embeddable SVG badge that prints the composite score of a shared audit report. Two JSON-RPC 2.0 surfaces carry the tool-driven side: one serves the portal, analyzer, and atlas rails for booking, identity checks, audits, and tool matching, and an Agent2Agent endpoint accepts tasks from another agent. Guests can call the open tools without a token, and an OpenID Connect token adds member tools and the account's own tier.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: ASignals: 4

99%

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).

60%

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.

40%

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: D-Signals: 4

16%

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.

55%

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.

100

Security

Trust, risk posture, and security compliance.

Grade: A+Signals: 1

100%

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: BSignals: 1

65%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the INITE AI Visibility to your agent

Capabilities

Start building with INITE AI Visibility API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

INITE AI Visibility

Jentic AI Readiness Score

INITE AI Visibility

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