Price Claude: production checklist for uncensored api

1. Verify the base URL and model ID

Your first step is confirming the API endpoint. We host our uncensored model at https://api.claudekey.cc/v1. This base URL works with the official OpenAI SDKs. Change the base URL and API key in your client configuration. Send requests to POST /v1/chat/completions. Use the model ID uncensored. This is an open-weight model tuned for freedom. It is not GPT, Claude, or Gemini. Verify this endpoint works before testing content.

Copycurl https://api.claudekey.cc/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List three reasons to use custom api keys for local models"}]
  }'

Check the response headers. Ensure the status is 200. This confirms the base URL is correct. Your client code should remain standard OpenAI format. Only the base URL and key change. This ensures compatibility with existing tools.

2. Confirm uncensored behavior with test prompts

The model answers without refusals for lawful adult content. Test it with prompts about complex topics. Check for refusals on standard queries. Send a request to the chat completions endpoint. Review the output for direct answers. The model is tuned for freedom. It does not refuse controversial or security-research topics. Verify this behavior early. It saves time during integration.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.claudekey.cc/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)

Test with diverse prompts. Include adult themes and niche topics. Ensure the model responds fully. This confirms the uncensored nature. It is crucial for NSFW LLM use cases. Verify the output matches your expectations.

3. Check token limits and context window

Our API supports a 100,000-token context window. This includes both prompt and completion. Max output is 16,000 tokens per request. If you do not set max_tokens, it defaults to 2,048. Check your request size. Large prompts may hit limits. Adjust your client settings accordingly. This prevents errors during high-volume use.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.claudekey.cc/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);

Monitor token usage. Track input and output tokens. Ensure your application handles large responses. This is critical for long-context tasks. Verify the limits match your needs.

4. Validate streaming and error handling

Streaming is supported via SSE. Token usage appears in the last chunk. Enable streaming in your SDK. Handle errors gracefully. Check for 4xx and 5xx responses. Errors are free, so test error paths. Verify the stream works correctly. This ensures real-time output. It is essential for chat applications.

Copystream = 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)

Test with invalid keys. Check the error message. Ensure your client handles it. Streaming adds responsiveness. Validate the chunk format. This confirms the API behavior.

5. Calculate your actual cost per request

Pricing is $0.15 per 1M input tokens. Output tokens cost $0.50 per 1M. Prepaid credit is charged by usage. Errors and refusals are free. No subscription fees. Calculate costs per request. Estimate token usage. This helps budget accurately. Crypto top-ups are required. USDT or USDC only.

Copycurl https://api.claudekey.cc/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List three reasons to use custom api keys for local models"}]
  }'

Track token counts. Monitor spending. Ensure credit covers usage. Trial credit is $0.50 for 7 days. This helps test before paying. Verify the cost model.

6. Monitor rate limits and concurrency

Rate limits are 300 requests per minute per key. Concurrency is 8 requests at once. Request body limit is 8 MB. Monitor these limits. Use a single key per account. Replace the key if needed. Track usage patterns. This prevents throttling. Ensure stable performance.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.claudekey.cc/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)

Check response headers for limits. Implement retry logic. Handle 429 errors. This ensures reliability. Verify the limits match your load.

7. Secure your claude key in production

Store your API key securely. Use environment variables. Do not expose it in client code. Rotate keys if needed. One active key per account. Sign up with Google or email. Key is shown immediately. No phone number needed. Protect the key. This prevents unauthorized use.

Copyimport OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.claudekey.cc/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);

Verify key permissions. Ensure it has access. Monitor for unusual activity. This keeps your account safe. Secure the key from the start.

8. Test function calling and JSON mode

Function calling is supported. Use tools and tool_choice. JSON mode is available with response_format json_object. Test these features. Ensure your client handles JSON. Verify function calls work. This adds structure to outputs.

Copycurl https://api.claudekey.cc/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "uncensored",
    "messages": [{"role": "user", "content": "List three reasons to use custom api keys for local models"}]
  }'

Check the response format. Ensure it parses correctly. This is crucial for integration. Verify the parameters. This ensures reliable data extraction.

9. Review privacy and data usage policy

Prompts are not used for training. Privacy is a key feature. No data training occurs. Verify this in the docs. Check the policy. Ensure it meets your needs. This is important for sensitive data. Confirm the privacy stance. This builds trust.

Copyfrom openai import OpenAI

client = OpenAI(base_url="https://api.claudekey.cc/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)

Review the terms. Ensure compliance. This protects your data. Verify the policy. This ensures privacy.