Official vendor OpenAPI document · agent-readyAI/MLLanguage Modelsbearer9 EndpointsREST
For Agents
Route chat, image, video, embedding, and speech requests to OpenAI, Anthropic Claude, Google Gemini, Qwen, and Doubao through one OpenAI-compatible gateway for AI agents.
Use for: Send a chat completion request to a Gemini model, Generate an image from a text prompt, Create a video and check its job status, Get text embeddings for a batch of documents
Not supported: Does not host or fine-tune models, manage billing, or store conversation history. Use for routing inference requests to upstream model providers only.
The 370.AI API is an OpenAI-compatible gateway that routes chat, image, video, embedding, and speech requests to upstream providers such as OpenAI, Anthropic Claude, Google Gemini, Alibaba Qwen, and ByteDance Doubao through one key and one base URL. Chat completions and a Claude-style messages endpoint accept the same request shape an OpenAI SDK already sends, so existing clients repoint without other changes. Image generation and editing, text-to-speech, and text embeddings are each a single call, and video generation runs as a job polled by id.
Install Jentic One Beta
Connect the 370.AI API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the 370.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.
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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%2F370.ai%2F370" | sh2
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%2F370.ai%2F370" | sh
jentic register # connects your agent to your Jentic One instanceJentic 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 370.AI API.
Send chat completion requests to OpenAI, Anthropic Claude, Google Gemini, Qwen, and Doubao through one key
Call a Claude-style messages endpoint with the same gateway credential
Generate images from a prompt and edit an existing image
Generate a video and poll the video job by its id
Create text embeddings and convert text to speech
List the models available through the gateway
Use Cases
Patterns agents use 370.AI API for, with concrete tasks.
★ AI agent with one model credential
An AI agent that needs several model providers would otherwise hold a separate key and client for each. Through Jentic the agent searches for 'send a chat completion', loads the 370.AI chat operation with its input schema, and sends an OpenAI-shaped request with the gateway key injected at call time. Switching the target model is a field in the body, not a new integration.
Call POST /v1/chat/completions with a chosen model and a prompt, then return the assistant message
Image and video generation
A content pipeline generates images from prompts and produces short videos. 370.AI exposes image generation and image editing as single calls, and video generation as a job that returns an id to poll. An agent can request a video, store the id, and check back until the render is ready.
Submit POST /v1/videos/generations, then poll GET /v1/videos/generations/{id} until the video job completes
Embeddings and speech for retrieval and voice
A retrieval system embeds documents and a voice feature reads answers aloud. 370.AI provides a text embeddings endpoint for semantic search and a text-to-speech endpoint, both behind the same gateway key. An agent can embed a corpus, then synthesise speech for a generated answer in the same session.
Create embeddings with POST /v1/embeddings for a document set, then synthesise an answer with POST /v1/audio/speech
Key Endpoints
9 endpoints — the 370.
METHOD
PATH
DESCRIPTION
POST
/v1/chat/completions
OpenAI-compatible chat completion
POST
/v1/messages
Claude-style messages request
POST
/v1/images/generations
Generate an image from a prompt
POST
/v1/videos/generations
Generate a video as a job
GET
/v1/videos/generations/{id}
Check a video job by id
GET
/v1/models
List available models
POST
/v1/embeddings
Create text embeddings
POST
/v1/audio/speech
Convert text to speech
POST
/v1/chat/completions
OpenAI-compatible chat completion
POST
/v1/messages
Claude-style messages request
POST
/v1/images/generations
Generate an image from a prompt
POST
/v1/videos/generations
Generate a video as a job
GET
/v1/videos/generations/{id}
Check a video job by id
GET
/v1/models
List available models
POST
/v1/embeddings
Create text embeddings
POST
/v1/audio/speech
Convert text to speech
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
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370.AI API
- AI-Aware (B+)67/100
75
Foundational Compliance70
Developer Experience & Jentic Compatibility58
AI-Readiness & Agent Experience94
Agent Usability60
Security56
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.2
Show dimension breakdown
75
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).
0%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
70
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: B+Signals: 4
45%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
33%
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.
58
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: C+Signals: 4
78%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
53%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
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.
60
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).
56
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: CSignals: 1
56%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring 370.AI by hand means issuing a gateway key, sending it as a bearer token, and choosing which provider model each request targets in the body. Through Jentic you install once, import 370.AI from the API Directory, store the key once, and your agent calls it.
Permission scoping
370.AI exposes a small set of operations under /v1 paths such as chat completions, image generation, and speech, so a rule can pin your agent to the operations it needs. You choose which it may call, so image, video, or speech generation is not included unless you add it.
Credential isolation
Your 370.AI gateway key is stored once, encrypted, by your own Jentic One instance and attached at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'send a chat completion' or 'generate an image', and Jentic returns the matching 370.AI operation with its input schema so the agent calls the right endpoint and sets the model it wants.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using 370.AI API through Jentic.
What authentication does the 370.AI API use?
370.AI authenticates with a bearer token per its OpenAPI spec: the gateway key is sent as an Authorization bearer header on each request, and keys are formatted as Bearer sk-... Through Jentic the key is held by your own instance and attached per call, so an agent routing requests never sees it.
Can I use my existing OpenAI client with the 370.AI API?
Yes. POST /v1/chat/completions accepts the same request shape an OpenAI SDK sends, so pointing the client at the gateway base URL is usually the only change. A Claude-style POST /v1/messages endpoint and GET /v1/models are also available for clients that prefer those shapes.
What are the rate limits for the 370.AI API?
The OpenAPI spec does not declare numeric rate limits, and effective limits depend on the upstream provider a request is routed to and your plan. Check the 370.AI documentation for current limits before running high-volume batch inference.
Is there a 370.AI MCP server?
You do not need a separate MCP server to use 370.AI with your agent. Jentic connects the gateway directly from the API Directory: import it, store your bearer key once, and your agent calls the chat, image, and speech operations on demand without loading another server's tool definitions into its context.
How do I generate a video through Jentic?
Search Jentic for 'generate a video', load the POST /v1/videos/generations operation to start the job, then poll GET /v1/videos/generations/{id} with the returned id until the render finishes. The key is attached by your instance. To run it on your own infrastructure, install Jentic One from its GitHub repo.
Can I limit which 370.AI operations my agent may call?
Yes. Write a rule that allows only the operations a task needs, such as chat completions and embeddings, so image, video, and speech generation stay out of reach unless you add them. The agent is bound to the operations you grant, and every call it makes through your instance is logged.
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