Install Jentic One Beta

Connect the Helicone API to your agent

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

Query logged LLM requests and their inputs

Attach scores, feedback, and custom properties to requests

Query agent sessions and their metrics

Manage prompts and prompt versions

Run and query prompt experiments and evaluators

GET STARTED

Start building with Helicone API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Helicone API for, with concrete tasks.

★ LLM Request Monitoring

An AI agent connected through Jentic can inspect how an LLM application is behaving. It queries logged requests, reads their inputs and scores, and pulls request metrics, so an assistant can surface error rates, latency, or cost trends without a separate dashboard session.

Query the most recent logged requests and summarize their error rate

Prompt Experimentation

Teams iterating on prompts need to compare versions against data. The Helicone API creates experiments, manages datasets, and runs evaluators over them, letting an agent set up a comparison and read back the scored results.

Create an experiment and run an evaluator over its dataset

Session Analytics

Multi-step agents produce sessions rather than single calls. The Helicone API queries sessions, their names, and aggregate metrics, so an agent can report on how a conversation or workflow performed end to end.

Query sessions and return their aggregate metrics

Key Endpoints

267 endpoints — the helicone api logs and analyzes large language model requests for llm applications.

METHOD

PATH

DESCRIPTION

POST

/v1/request/query

Query logged LLM requests

GET

/v1/request/{requestId}

Get a logged request by ID

POST

/v1/session/query

Query agent sessions

POST

/v1/experiment/query

Query prompt experiments

POST

/v1/prompt-2025/query

Query prompts

GET

/v1/models

List models

POST

/v1/request/query

Query logged LLM requests

GET

/v1/request/{requestId}

Get a logged request by ID

POST

/v1/session/query

Query agent sessions

POST

/v1/experiment/query

Query prompt experiments

POST

/v1/prompt-2025/query

Query prompts

GET

/v1/models

List models

Why Jentic?

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

Setup

Wiring Helicone by hand means creating an API key, building request and session queries, and paging through large result sets yourself. Through Jentic you install once, import Helicone from the API Directory, store the key once, and your agent calls the query and management operations directly.

Permission scoping

You choose which of the operations your agent may call and can keep it to read-only queries. You might allow request and session queries while blocking key management and prompt edits.

Credential isolation

Your Helicone API 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 'query logged LLM requests', and Jentic returns the matching Helicone operation with its input schema so the agent calls it with the right filters.

FAQs

Specific to using Helicone API through Jentic.

What authentication does the Helicone API use?

Most operations authenticate with an API key sent as a Bearer token in the Authorization header, per the OpenAPI spec. A few public endpoints, such as the model list, need no key. Through Jentic the key is stored once, encrypted, by your own self-hosted instance and injected when the agent calls, so it never appears in the agent's prompt or logs.

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

Yes. You choose which operations the agent may call and can keep it to read-only queries. You might allow request and session queries while blocking key management and prompt edits, with every call logged by your own instance.

Is there a Helicone MCP server?

You don't need an MCP server to give your agent the Helicone API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent calls the request, session, and experiment operations. Operations are discovered on demand, so nothing extra loads into the agent's context.

What are the rate limits for the Helicone API?

The OpenAPI spec does not define rate limits. Check the Helicone documentation for current plan limits before running high-volume queries against the request logs.

What can I do with the Helicone API?

You can query logged LLM requests and their inputs, attach scores and feedback, group calls into sessions with metrics, manage prompts and their versions, run experiments and evaluators, and administer provider and API keys.

How do I query LLM request logs through Jentic?

Search Jentic by intent, for example 'query logged LLM requests', and Jentic returns the matching Helicone operation with its input schema. Your agent supplies the filters and reads back the matching requests. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Helicone API

Name: Helicone API
Brand: Helicone API
Availability: InStock

Official vendor OpenAPI document · agent-readyDeveloper ToolsMonitoring ObservabilityapiKey267 EndpointsREST

For Agents

Query logged LLM requests, score and annotate them, group calls into sessions, manage prompts and experiments, and run evaluators. Authenticates with an API key sent as a Bearer token in the Authorization header.

Use for: Query the most recent logged LLM requests, Get a logged request by its identifier, Attach a score to a logged request, List agent sessions and their metrics

Not supported: Does not run model inference itself. Use the Helicone API to log, query, and analyze LLM usage and to manage prompts, experiments, and keys.

The Helicone API logs and analyzes large language model requests for LLM applications. It queries logged requests and their inputs, attaches scores, feedback, and custom properties, groups calls into agent sessions with metrics, manages prompts and prompt versions, runs prompt experiments and evaluators, and administers provider keys and API keys.

Jentic One on Github View OpenAPI Document

Connect the Helicone API to your agent

Capabilities

Start building with Helicone API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Helicone API