Install Jentic One Beta

Connect the Prism Inference API to your agent

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

Generate chat completions in OpenAI Chat Completions format with model, messages, tools, and response_format

Create responses in OpenAI Responses format with instructions, previous_response_id chaining, and background runs

Send Anthropic Messages format requests with system, max_tokens, tools, and thinking settings

Count input tokens for an Anthropic-style messages request before sending it

GET STARTED

Start building with Prism Inference API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Prism Inference API for, with concrete tasks.

★ Agent model calls through one gateway

An AI agent that delegates sub-tasks to a language model can call Prism without its own client library. Through Jentic the agent searches for 'create a chat completion', loads createChatCompletion with its input schema, and sends model and messages, with the credential injected at call time. Because Prism also speaks the Anthropic Messages and OpenAI Responses formats, the agent can use whichever request shape its prompts were written for.

GET /v1/models to pick a model id, then POST /v1/chat/completions with that model and a messages array containing a user message asking for a three-line summary

Drop-in provider switch for existing apps

An application built on the OpenAI or Anthropic SDK can move its traffic to Prism by changing the base URL, since the request bodies follow the same formats. Chat Completions calls require model and messages, Responses calls require model and input, and Messages calls require model, max_tokens, messages, and the anthropic-version header, so existing payloads carry over.

POST /v1/messages with anthropic-version '2023-06-01', a model id, max_tokens 512, and a messages array, and compare the output with the same prompt sent to /v1/chat/completions

Token budgeting before a long prompt

Long-context work needs to know whether a prompt fits before spending on generation. countMessageTokens takes the same model, messages, system, and tools fields as a Messages request and returns the input token count, so a pipeline can trim or split documents before calling createMessage.

POST /v1/messages/count_tokens with a model id, a system prompt, and a messages array holding a long document, and split the document if the count exceeds the budget

Key Endpoints

10 endpoints — the prism inference api serves language model inference behind three wire formats at once: openai chat completions, openai responses, and anthropic messages.

METHOD

PATH

DESCRIPTION

POST

/v1/chat/completions

Create a chat completion

POST

/v1/responses

Create a response

POST

/v1/messages

Create a message

POST

/v1/messages/count_tokens

Count message input tokens

GET

/v1/models

List models

GET

/v1/models/{model}

Retrieve a model

POST

/v1/chat/completions

Create a chat completion

POST

/v1/responses

Create a response

POST

/v1/messages

Create a message

POST

/v1/messages/count_tokens

Count message input tokens

GET

/v1/models

List models

GET

/v1/models/{model}

Retrieve a model

Why Jentic?

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

Setup

Wiring Prism by hand means picking between bearer and x-api-key auth, setting the anthropic-version header on Messages calls, and handling three different request and streaming formats. Through Jentic you install once, import Prism Inference from the API Directory, store the key once, and your agent calls it.

Permission scoping

Prism separates its formats by route (/v1/chat/completions, /v1/responses, /v1/messages), and the model is chosen in the request body, so rules bound which routes your agent may call rather than which model it uses. You choose the operations, so the agent can be limited to one format plus the public model listing.

Credential isolation

Your Prism key is stored once, encrypted, by your own Jentic One instance and injected into the request at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'create a chat completion' or 'count prompt tokens', and Jentic returns the matching Prism operation with its input schema, including the required model and messages fields, so the agent calls the right endpoint directly.

FAQs

Specific to using Prism Inference API through Jentic.

What authentication does the Prism Inference API use?

Per its OpenAPI spec, the Prism Inference API accepts either a bearer token in the Authorization header or an API key in the x-api-key header on its generation and token-counting routes. The API information, health, and model listing routes are public endpoints that need no credential. Through Jentic the credential is held by your own instance and attached at call time.

Can I use the Anthropic Messages format with the Prism Inference API?

Yes. POST /v1/messages accepts the Anthropic Messages shape with model, max_tokens, and messages required, plus optional system, tools, tool_choice, and thinking, and it requires the anthropic-version header, which defaults to 2023-06-01. POST /v1/messages/count_tokens counts input tokens for the same shape.

What are the rate limits for the Prism Inference API?

The OpenAPI spec does not specify rate limits. Check the Prism documentation at https://docs.prisminference.com for current limits per account.

Is there a Prism Inference MCP server?

You don't need an MCP server to give your agent the Prism Inference API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent calls the completion and messages operations on demand without loading another server's tool definitions into its context.

How do I run a chat completion through Jentic with the Prism Inference API?

Search Jentic for 'create a chat completion', load createChatCompletion, and execute it with a model id from GET /v1/models and a messages array. Set stream to true if the agent should receive output incrementally. To run it on your own infrastructure, install Jentic One from its GitHub repo.

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

Yes. Write a rule that allows only POST /v1/chat/completions and GET /v1/models, so the agent can generate text in one format and look up models but not call the Responses or Messages routes. The model choice travels in the request body, so the rule bounds the routes, not which model is used. Every call it makes is logged for review.

Prism Inference API

AI ReadinessFoundational (C+)58/100

See full scorecard

Official vendor OpenAPI document · agent-readyAI/MLLanguage Modelsbearer, apiKey10 EndpointsREST

For Agents

Run chat completions, Responses API calls, or Anthropic-style messages against Prism-hosted models with one credential, and count input tokens before sending.

Use for: I need to run a chat completion with an OpenAI-compatible client, Send an Anthropic Messages request to a different inference provider, List all models available on Prism, Count the input tokens in my prompt before sending it

Not supported: Does not fine-tune models, generate embeddings, or create images or audio. Use for text generation through OpenAI- and Anthropic-compatible routes only.

The Prism Inference API serves language model inference behind three wire formats at once: OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages. Existing clients written for either provider can point at the Prism host and send the same model and messages payloads, with streaming, tool calling, response_format, and reasoning or thinking controls where each format supports them. A token-counting route sizes Anthropic-style requests before sending, and public model routes list and describe the models available.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

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).

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: FSignals: 4

12%

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.

48%

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: CSignals: 1

55%

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: CSignals: 1

54%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Prism Inference API to your agent

Capabilities

Start building with Prism Inference API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Prism Inference API

Jentic AI Readiness Score

Prism Inference 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