Install Jentic One Beta

Connect the Needle fine-tuning API to your agent

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

Draft tool definitions from a plain product description

Generate training, validation, and test files from tool definitions

Start a fine-tune of Needle 3 and poll its status per depth

Download a fine-tuned model as a .cact file via a signed link

Upload your own files and list the ones you generate

GET STARTED

Start building with Needle fine-tuning API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Needle fine-tuning API for, with concrete tasks.

★ Agent-run fine-tuning pipeline

An AI agent can take a product description, draft tool definitions from it, generate the training, validation, and test files, start a Needle 3 fine-tune, and poll the job until it succeeds. Each step is a separate call the agent chains, and the fine-tune reports evaluations per depth.

Draft tool definitions from a product description, generate the training files, and start a Needle 3 fine-tune

Model download and deployment

Once a fine-tune succeeds, an agent can retrieve the model and download it as a .cact file through a short-lived signed link, ready to run on device. The models endpoint lists the base needle-3 model first, then any fine-tuned sizes.

List the available models, then download the latest fine-tuned model as a .cact file

Training-data generation

A developer can draft tool definitions from a description and generate a training, validation, and test split without starting a fine-tune, using the generation job to produce data they inspect first. Draft tool definitions are limited to a set number per day.

Draft tool definitions and generate a training/validation/test split, then list the generated files

Key Endpoints

27 endpoints — the needle api generates tool-calling training data, fine-tunes the needle 3 model on it, and serves the resulting models for download.

METHOD

PATH

DESCRIPTION

POST

/tool_schemas

Draft tool definitions from a description

POST

/generations

Generate training, validation, and test files

POST

/fine_tuning/jobs

Start a fine-tune

GET

/fine_tuning/jobs/{job_id}

Retrieve a fine-tune's status

GET

/models/{model_id}/content

Download a model .cact file

POST

/api_keys

Create an API key

POST

/tool_schemas

Draft tool definitions from a description

POST

/generations

Generate training, validation, and test files

POST

/fine_tuning/jobs

Start a fine-tune

GET

/fine_tuning/jobs/{job_id}

Retrieve a fine-tune's status

GET

/models/{model_id}/content

Download a model .cact file

POST

/api_keys

Create an API key

Why Jentic?

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

Setup

Wiring Needle by hand means handling its bearer-token auth and the multi-step flow from drafting tool definitions through generation, fine-tuning, and the signed download link. Through Jentic you install once, import Needle from the API Directory, store the token once, and your agent calls it.

Permission scoping

You choose which Needle operations the agent may call, such as generation and fine-tune reads, so destructive operations like deleting a model or revoking a key are not included unless you add them.

Credential isolation

Your Needle 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 'fine-tune a tool-calling model', and Jentic returns the matching Needle operation with its input schema so the agent sequences the flow without reading the docs.

FAQs

Specific to using Needle fine-tuning API through Jentic.

What authentication does the Needle fine-tuning API use?

The Needle API authenticates with a bearer token in the Authorization header, per its OpenAPI spec. The plans endpoint is open, but creating keys, generating data, and fine-tuning all require the token.

Is there a Needle MCP server?

You do not need an MCP server to give your agent Needle. Jentic connects it directly from the API Directory: import it, store your key once, and your agent calls the generation, fine-tune, and model operations without loading another server's tool definitions into its context.

Can I limit what my agent is allowed to do with the Needle fine-tuning API?

Yes. Write a rule that allows only the generation and fine-tune read operations, so the agent can build data and check job status but cannot delete a model or revoke a key until you add those operations, and every call it makes is logged.

Can I download a fine-tuned model with the Needle fine-tuning API?

Yes. Once a fine-tune succeeds, the model content endpoint returns a short-lived signed link to the .cact file, so an agent can fetch the finished model and run it on device.

What are the rate limits for the Needle fine-tuning API?

The OpenAPI spec notes that drafting tool definitions is limited per day, and fine-tunes spend a run from your plan allowance. Read the billing endpoint for your plan, limits, and usage this period.

How do I fine-tune a model with the Needle fine-tuning API through Jentic?

Search Jentic for 'fine-tune a tool-calling model', and it returns the Needle fine-tune operation with its input schema. Draft tool definitions, generate the files, start the fine-tune, and download the result. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Cactuscompute Needle fine-tuning API

AI ReadinessFoundational (D)43/100

See full scorecard

Official vendor OpenAPI document · agent-readyAI/MLMl Inferencebearer27 EndpointsREST

For Agents

Draft tool definitions, generate training data, fine-tune Needle 3, and download the resulting tool-calling model as a .cact file.

Use for: Draft tool definitions from a product description, Generate training and validation files from my tool definitions, Start a fine-tune of Needle 3, Check the status of a running fine-tune job

Not supported: Does not handle chat completion, image generation, or model hosting for inference. Use for tool-calling data generation, Needle 3 fine-tuning, and model download only.

The Needle API generates tool-calling training data, fine-tunes the Needle 3 model on it, and serves the resulting models for download. You draft tool definitions from a product description, generate training, validation, and test files, start a fine-tune, and download the finished model as a signed link. Files, generation jobs, fine-tunes, and API keys each have their own management operations.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A-Signals: 4

97%

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).

10%

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: B-Signals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

48%

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

20%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

OperationId Quality

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

57%

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: C+Signals: 1

59%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Needle fine-tuning API to your agent

Capabilities

Start building with Needle fine-tuning API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Cactuscompute Needle fine-tuning API

Jentic AI Readiness Score

Needle fine-tuning 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