Install Jentic One Beta

Connect the EduChecker to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the EduChecker, 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%2Feduchecker.io%2Feduchecker" | 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%2Feduchecker.io%2Feduchecker" | 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 EduChecker API.

Create a check that runs ML fraud detection on an uploaded diploma

Retrieve a check's status and a heatmap highlighting suspected tampering

Run a quick AI authenticity check without persisting the document

Submit institution-based verification requests against a country's issuing bodies

Export a check's data and retrieve the original document file

GET STARTED

Start building with EduChecker API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use EduChecker API for, with concrete tasks.

★ AI Agent Credential Verification

Let an AI agent screen submitted diplomas for fraud as part of a hiring or admissions workflow: it creates a check on the uploaded document, polls the status until the ML models finish, and retrieves the heatmap that marks suspected tampering. Through Jentic the agent discovers the right EduChecker operation by intent and calls it with the check id, so verification runs without a developer wiring the create-and-poll flow by hand.

Create a check for an uploaded diploma, poll its status until complete, then retrieve the fraud-detection heatmap

Quick Authenticity Screening

High-volume reviewers want a fast first pass before committing to a full persisted check. The quick AI check operation screens a diploma image for signs of tampering and returns a result without storing the document. An agent uses it to triage obvious fakes and only escalates borderline cases to a full check.

Run a quick AI check on a diploma image to screen for tampering before creating a persisted check

Institution-Based Verification

Some credentials need confirmation directly from the issuing institution rather than ML alone. The API lists the institutions and verification channels available for a country, submits a verification request against the issuing body, and tracks the request to completion. This routes a credential to an authoritative source when document analysis is not enough.

List the institutions for a country, submit a verification request against the issuing institution, then poll the request status

Bulk Check Management

Teams processing many credentials manage checks in batches and keep records only as long as needed. The API lists a user's checks, exports data for completed ones, and bulk-deletes checks that are no longer required. An agent uses this to reconcile a backlog and enforce a retention policy.

List a user's checks, export the data for completed ones, then bulk-delete the checks that are no longer needed

Key Endpoints

94 endpoints — the educhecker api detects diploma and academic-credential fraud using machine-learning models.

METHOD

PATH

DESCRIPTION

POST

/api/checks/

Create a diploma check

GET

/api/checks/{check_id}

Get a check's status

GET

/api/checks/{check_id}/heatmap

Get a check's tampering heatmap

POST

/api/ai/quick

Run a quick AI authenticity check

POST

/api/verification/requests

Create an institution verification request

GET

/api/verification/institutions

List institutions for verification

GET

/api/checks/{check_id}/document

Get the original document file

GET

/api/checks/{check_id}/export

Export a check's data

POST

/api/checks/

Create a diploma check

GET

/api/checks/{check_id}

Get a check's status

GET

/api/checks/{check_id}/heatmap

Get a check's tampering heatmap

POST

/api/ai/quick

Run a quick AI authenticity check

POST

/api/verification/requests

Create an institution verification request

GET

/api/verification/institutions

List institutions for verification

GET

/api/checks/{check_id}/document

Get the original document file

GET

/api/checks/{check_id}/export

Export a check's data

Why Jentic?

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

Setup

Wiring EduChecker by hand means handling its bearer-token auth, the create-check-then-poll-status verification flow, and its billing and credit model before a check runs. Through Jentic you install once, import EduChecker from the API Directory, store the token once, and your agent calls it.

Permission scoping

EduChecker puts the check id in the URL path (/api/checks/{check_id}), so a rule can pin your agent to specific checks and the operations you pick. You choose the operations it may call, so creating checks and reading their status can be allowed while destructive ones like permanently deleting a check or bulk-deleting checks are not included unless you add them.

Credential isolation

Your EduChecker 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 'verify a diploma' or 'run a fraud check', and Jentic returns the matching EduChecker operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using EduChecker API through Jentic.

What authentication does the EduChecker API use?

The EduChecker API authenticates with a bearer token per its OpenAPI spec, obtained by registering and logging in through its auth operations, including Google sign-in. Through Jentic the token is stored encrypted by your own Jentic One instance and injected at call time, so it never enters the agent's context.

Can I detect diploma fraud with the EduChecker API?

Yes. The create-check operation runs ML fraud detection on an uploaded diploma, and you poll the check status and retrieve a heatmap that highlights suspected tampering. A quick AI check operation screens a document for authenticity without persisting it.

What are the rate limits for the EduChecker API?

The OpenAPI spec does not specify rate limits; see https://educhecker.io for current limits. Checks are also governed by your credit and subscription balance, which you can read with the credits and usage operations.

Is there an EduChecker MCP server?

You don't need an MCP server to give your agent the EduChecker API. Jentic connects it directly from the API Directory: import it, store your token once, and your agent calls operations like creating a check or reading its heatmap. Operations are discovered on demand, so no extra server's tool definitions sit in your agent's context.

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

Yes. Write a rule that allows only creating checks and reading their status and heatmaps, so the agent can submit documents and read results but cannot permanently delete checks or bulk-delete them. Because EduChecker addresses each check by id in the URL path, a rule can also pin the agent to specific checks, and every call is logged.

How do I verify a diploma with the EduChecker API through Jentic?

Search Jentic for 'verify a diploma for fraud' to find the create-check operation, upload the document, poll the check status, then read the fraud-detection heatmap. To run it on your own infrastructure, install Jentic One from its GitHub repo.

EduChecker

AI ReadinessFoundational (C+)58/100

See full scorecard

Community OpenAPI document · agent-readyIdentity AuthIdentity Verificationbearer94 EndpointsREST

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For Agents

Run ML-based diploma fraud detection: create a check on a document, read its status and tampering heatmap, or run a quick AI authenticity check. Covers 94 operations across checks, verification requests, and billing.

Use for: Create a check to verify a diploma's authenticity, Get the status of a diploma fraud check, Retrieve the tampering heatmap for a check, Run a quick AI authenticity check on a document

Not supported: Does not handle background checks, employment history, or identity-document issuance. Use for diploma and academic-credential fraud detection only.

The EduChecker API detects diploma and academic-credential fraud using machine-learning models. Agents create a check on an uploaded document, poll its status, and retrieve a heatmap that highlights suspected tampering, or run a quick AI authenticity check without persisting the document. Institution-based verification requests can be submitted against a country's issuing bodies, and results exported once complete. Authentication uses a bearer token, and the API also covers billing, credits, accounts, and notifications around the verification workflow.

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: B-Signals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

45%

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

24%

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.

52%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: ASignals: 1

86%

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: A-Signals: 1

71%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the EduChecker to your agent

Capabilities

Start building with EduChecker API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

EduChecker

Jentic AI Readiness Score

EduChecker

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