How do I authenticate my uncensored AI tool requests?

Pass your API key in the Authorization header as a Bearer token. You receive this key immediately after signing up with Google or email. Use it for all subsequent requests to the base URL.

What happens if I hit the rate limit?

The API returns a 429 status code. You can make 300 requests per minute per key. Increase your throughput by using multiple keys or adjusting your request frequency.

Can I use this uncensored coding API for structured data?

Yes. Enable JSON mode or use function calling tools. The model returns valid JSON objects that parse reliably in your application. This is ideal for automated data extraction tasks.

Documentation: Integrate the Uncensored AI Tool API

Base URL and Authentication

Start every request by pointing your SDK to our base URL.

HTTPS://api.uncensoredaitool.com/v1

Include your API key in the Authorization header. We issue one key per account immediately after signup. Rotate keys freely since they replace older ones.

No monthly fees apply.
Auth uses Bearer tokens.

curl https://api.uncensoredaitool.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "list all linux kernel panic reasons"}]
  }'

Sending Requests: POST /v1/chat/completions

Post JSON payloads to the chat completions endpoint.

Define your model as "uncensored". Pass messages in the standard array format. The API returns text responses instantly. Use this uncensored LLM API for roleplay or data extraction.

from openai import OpenAI

client = OpenAI(base_url="https://api.uncensoredaitool.com/v1", api_key="YOUR_KEY")

resp = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Summarise this thread without softening it."}],
)
print(resp.choices[0].message.content)

Streaming Responses via SSE

Enable streaming by setting stream to true.

Receive Server-Sent Events (SSE) containing partial text chunks. Token usage details appear in the final chunk. This method reduces perceived latency for long outputs.

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.uncensoredaitool.com/v1", apiKey: process.env.API_KEY });

const resp = await client.chat.completions.create({
  model: "uncensored",
  messages: [{ role: "user", content: "Draft a villain monologue for my game." }],
});
console.log(resp.choices[0].message.content);

Function Calling and JSON Mode

Use the model for structured data extraction.

Pass a schema in the tools parameter. The API returns structured JSON objects. Enable strict JSON mode with response_format for reliable parsing. This works well for coding tasks or form data generation.

stream = client.chat.completions.create(
    model="uncensored",
    messages=[{"role": "user", "content": "Tell the story in second person."}],
    stream=True,
)
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Parameters: Temperature, Top-P, and Stop Sequences

Control creativity and output boundaries.

Set temperature for randomness. Adjust top_p for nucleus sampling. Define stop sequences to halt generation at specific markers. Seed values ensure reproducible results for testing.

Model ID and Context Window Limits

Set model to "uncensored".

The context window supports 100,000 tokens total. Maximum output is 16,000 tokens per request. Errors and refusals consume no credit. Requests exceeding limits return 400 errors.

Uncensored AI API Documentation