Install Jentic One Beta

Connect the AI Wave API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the AI Wave 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%2Felopstudio.com%2Felopstudio" | 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%2Felopstudio.com%2Felopstudio" | 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 AI Wave API.

Read a normalized feed of AI model changes across vendors and sources

List tracked models and read per-model price history

Get a daily digest of what changed across models

Estimate token cost for a model from the catalog

GET STARTED

Start building with AI Wave API

Explore with Jentic One

View OpenAPI Document

Use Cases

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

★ Agent that reacts to model changes

An agent keeps its model choices current. Through Jentic the agent registers a webhook and reads the normalized change feed, so when a model is released, repriced, or deprecated across vendor notes, Hugging Face, OpenRouter, or GitHub, the agent learns about it and can switch. Duplicate entries for the same model are already collapsed.

Model price monitoring

A team watches what its models cost over time. The model list and per-model price-history calls return how pricing has moved, and the daily digest summarizes the day's changes, so a workflow can chart price trends and catch an increase. Pricing comes from the OpenRouter public catalog.

Read a model's price history, compare it with the daily digest, and report any model whose price rose

Cost estimation before a run

An agent estimates spend before it commits. The estimate operation returns a token-cost estimate for a model drawn from the catalog, so a workflow can compare candidate models on price before routing a prompt. The model list supplies the identifiers to estimate against.

Estimate the token cost for a prompt on two candidate models and return the cheaper one

Key Endpoints

10 endpoints — the ai wave api delivers a single normalized feed of ai model changes, merging vendor release notes, hugging face uploads, the openrouter catalog, and github, and collapsing duplicate entries for the same model.

METHOD

PATH

DESCRIPTION

GET

/api/v1/changes

Read the model change feed

GET

/api/v1/models

List tracked models

GET

/api/v1/models/{slug}/history

Read a model's price history

GET

/api/v1/digest

Get today's digest of changes

POST

/api/v1/estimate

Estimate token cost for a model

POST

/api/webhooks

GET

/api/webhooks

List webhook addresses

DELETE

/api/webhooks/{id}

Remove a webhook

GET

/api/v1/changes

Read the model change feed

GET

/api/v1/models

List tracked models

GET

/api/v1/models/{slug}/history

Read a model's price history

GET

/api/v1/digest

Get today's digest of changes

POST

/api/v1/estimate

Estimate token cost for a model

POST

/api/webhooks

GET

/api/webhooks

List webhook addresses

DELETE

/api/webhooks/{id}

Remove a webhook

Why Jentic?

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

Setup

Wiring the AI Wave API by hand means handling its bearer key, reconciling model names across vendor notes, Hugging Face, OpenRouter, and GitHub, and managing webhook subscriptions yourself. Through Jentic you install once, import AI Wave from the API Directory, store the key once, and your agent calls it.

Permission scoping

AI Wave is mostly read-only, and its webhook id travels in the URL path (/api/webhooks/{id}), so a rule bounds your agent to the operations it needs: reading the change feed, model list, and price history. Registering or removing webhooks is not included unless you add it.

Credential isolation

Your AI Wave 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 'get today's model changes' or 'read a model's price history', and Jentic returns the matching AI Wave operation with its input schema so the agent calls the right endpoint without reading the reference docs.

FAQs

Specific to using AI Wave API through Jentic.

What authentication does the AI Wave API use?

The AI Wave API authenticates with a bearer API key per its OpenAPI spec, issued from your member dashboard and sent as `Authorization: Bearer ...`. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never enters the agent's context.

Is there an AI Wave MCP server?

You don't need to wire a separate MCP server to give your agent the AI Wave API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent reads the change feed and price history on demand without loading extra tool definitions into its context.

Can I track a model's price history with the AI Wave API?

Yes. The model list returns the models AI Wave tracks, and a per-model history call returns its pricing over time. A daily digest summarizes what changed, and you can register a webhook to be notified when a model moves.

What are the rate limits for the AI Wave API?

The OpenAPI spec does not state specific rate limits. Check the provider's documentation at https://aiwave.elopstudio.com for the limits that apply to your key before polling the change feed heavily.

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

Yes. Write a rule that allows only the read operations your agent needs, such as the change feed, model list, and price history, so registering or removing webhooks stays out of its reach. Every call it makes is logged.

How do I get today's model changes with the AI Wave API through Jentic?

Search Jentic for 'get today's AI model changes' and it returns the digest operation with its input schema; your agent reads back the day's released, repriced, and deprecated models. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Elopstudio AI Wave API

AI ReadinessAI-Aware (B-)61/100

See full scorecard

Official vendor OpenAPI document · agent-readyDeveloper ToolsMonitoring Observabilitybearer10 EndpointsREST

For Agents

Track AI model changes in one normalized feed: new releases, price history, and a daily digest across vendor notes, Hugging Face, OpenRouter, and GitHub, with webhooks for updates and a token-cost estimate.

Use for: Get today's digest of AI model changes, List the models AI Wave tracks, Check the price history for a specific model, Register a webhook for model changes

Not supported: Does not run inference, host models, or route prompts. Use for tracking AI model changes, pricing history, and cost estimates only.

The AI Wave API delivers a single normalized feed of AI model changes, merging vendor release notes, Hugging Face uploads, the OpenRouter catalog, and GitHub, and collapsing duplicate entries for the same model. It serves a change feed, a model list, and per-model price history, a daily digest of what moved, and a token-cost estimate, and it registers webhooks so a change pushes to your endpoint. Pricing and context values come from the OpenRouter public catalog, so when only those are needed the source can be called directly.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A-Signals: 4

96%

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).

100%

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: BSignals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

53%

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

41%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

90%

OperationId Quality

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

53%

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: D+Signals: 1

49%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the AI Wave API to your agent

Capabilities

Start building with AI Wave API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Elopstudio AI Wave API

Jentic AI Readiness Score

AI Wave 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