Install Jentic One Beta

Connect the Respan AI API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Respan 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.

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%2Fapi.respan.ai%2Frespan-ai" | 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%2Fapi.respan.ai%2Frespan-ai" | 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 Respan AI API.

Run chat completions against large language models

Send a conversation of messages and receive the model's reply

Select the model and generation parameters for each request

Use Cases

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

★ LLM-Backed Agent

An AI agent uses Respan AI as its language-model backend, sending a conversation of messages and reading back the completion to drive its next step. Through Jentic the agent discovers the chat completions operation by intent and calls it directly, so it can reason and generate text without a provider SDK wired into the app.

GET STARTED

Start building with Respan AI API

Explore with Jentic One

View OpenAPI Document

Content Generation

Generate drafts, summaries, or replies by sending a prompt and reading the model's response. This lets an agent produce copy on demand while the model and parameters stay under the caller's control, keeping output consistent across requests.

Summarize a block of text into three bullet points using a chosen model

Structured Extraction

Turn unstructured text into structured fields by prompting the model to return a defined shape. The agent sends the text and instructions and parses the completion, extracting values without a dedicated parser for each format.

Prompt the model to extract a name and date from a sentence and return them as JSON

Key Endpoints

1 endpoints — jentic publishes the only available openapi specification for the respan ai api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/chat/completions

Run a chat completion

POST

/chat/completions

Run a chat completion

Why Jentic?

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

Setup

Wiring the Respan AI API by hand means handling its bearer-token auth and the OpenAI-compatible request shape yourself. Through Jentic you install once, import Respan AI from the API Directory, store the token once, and your agent calls it.

Permission scoping

Respan AI exposes one chat completions operation, so scoping is about whether the agent may call it, not which record it touches. You allow that operation explicitly, and every call it makes is logged.

Credential isolation

Your Respan AI 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 'run a chat completion', and Jentic returns the Respan AI chat completions operation with its input schema so the agent calls the model without browsing the reference docs.

FAQs

Specific to using Respan AI API through Jentic.

What authentication does the Respan AI API use?

The Respan AI API authenticates with a bearer token in the Authorization header, per its OpenAPI spec. 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 prompt or logs.

Can I run a chat completion with the Respan AI API?

Yes. Call POST /chat/completions with a list of messages and the model you want. The endpoint is OpenAI-compatible, so a conversation and model parameters return the model's generated reply.

What are the rate limits for the Respan AI API?

The OpenAPI spec does not specify rate limits. Check the Respan AI documentation at https://api.respan.ai before sending high-volume completion traffic.

Why is there no official OpenAPI spec for the Respan AI API?

Respan AI does not publish its own OpenAPI description. Jentic maintains this specification from the documented chat completions endpoint and keeps it validated so agents can call the API reliably.

Is there a Respan AI MCP server?

You don't need an MCP server to give your agent the Respan AI API. Jentic connects it directly from the API Directory: import it, store your token once, and your agent calls the chat completions operation.

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

Yes. Respan AI exposes a single chat completions operation, so a rule controls whether the agent may call it at all, and every call it makes is logged.

How do I run a chat completion with the Respan AI API through Jentic?

Search Jentic for 'run a chat completion', and it returns the POST /chat/completions operation with its input schema so your agent calls the model directly. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Respan AI API

Name: Respan AI API
Brand: Respan AI API
Availability: InStock

Agent-ready OpenAPI document · curated by JenticAI/MLLanguage Modelsbearer1 EndpointsREST

Know of an official OpenAPI document? Contribute it →

For Agents

Run chat completions against large language models through an OpenAI-compatible endpoint. Send a conversation of messages with the model and generation parameters and receive the model's reply.

Use for: Generate a chat completion from a prompt, Continue a multi-turn conversation with an LLM, Summarize text with a language model, Draft a reply using a chosen model

Not supported: Does not handle model fine-tuning, embeddings, or file storage. Use for running chat completions against large language models only.

Jentic publishes the only available OpenAPI specification for the Respan AI API, keeping it validated and agent-ready. The Respan AI API runs chat completions against large language models through a single OpenAI-compatible endpoint. It accepts a conversation of messages along with the model and generation parameters and returns the model's reply, so an agent can call an LLM without wiring a provider SDK.

Jentic One on Github View OpenAPI Document