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Documentation Index

Fetch the complete documentation index at: https://docs.cline.bot/llms.txt

Use this file to discover all available pages before exploring further.

The Cline API is OpenAI-compatible, so any library or tool that works with OpenAI also works with the Cline API. Just change the base URL and API key.

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curl

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Non-Streaming

curl -X POST https://api.cline.bot/api/v1/chat/completions \
  -H "Authorization: Bearer $CLINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-6",
    "messages": [{"role": "user", "content": "What is 2+2?"}],
    "stream": false
  }'

​
Streaming

curl -X POST https://api.cline.bot/api/v1/chat/completions \
  -H "Authorization: Bearer $CLINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-6",
    "messages": [{"role": "user", "content": "Write a short poem about code."}],
    "stream": true
  }'

​
Python

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OpenAI SDK

The OpenAI Python SDK works with the Cline API by setting base_url: 
from openai import OpenAI

client = OpenAI(
    base_url="https://api.cline.bot/api/v1",
    api_key="YOUR_API_KEY",
)

# Non-streaming
response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Explain recursion in one sentence."}],
)
print(response.choices[0].message.content)

​
Streaming in Python

from openai import OpenAI

client = OpenAI(
    base_url="https://api.cline.bot/api/v1",
    api_key="YOUR_API_KEY",
)

stream = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Write a function to reverse a string in Python."}],
    stream=True,
)

for chunk in stream:
    content = chunk.choices[0].delta.content
    if content:
        print(content, end="", flush=True)
print()

​
Tool Calling in Python

from openai import OpenAI
import json

client = OpenAI(
    base_url="https://api.cline.bot/api/v1",
    api_key="YOUR_API_KEY",
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get weather for a location",
            "parameters": {
                "type": "object",
                "properties": {
                    "location": {"type": "string", "description": "City name"}
                },
                "required": ["location"],
            },
        },
    }
]

response = client.chat.completions.create(
    model="anthropic/claude-sonnet-4-6",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    tools=tools,
)

# Check if the model wants to call a tool
choice = response.choices[0]
if choice.message.tool_calls:
    tool_call = choice.message.tool_calls[0]
    print(f"Tool: {tool_call.function.name}")
    print(f"Args: {tool_call.function.arguments}")

​
Using requests

If you prefer not to use the OpenAI SDK: 
import requests

response = requests.post(
    "https://api.cline.bot/api/v1/chat/completions",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={
        "model": "anthropic/claude-sonnet-4-6",
        "messages": [{"role": "user", "content": "Hello!"}],
        "stream": False,
    },
)

data = response.json()
print(data["choices"][0]["message"]["content"])

​
Node.js / TypeScript

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OpenAI SDK

The OpenAI Node.js SDK works with the Cline API by setting baseURL: 
import OpenAI from "openai"

const client = new OpenAI({
  baseURL: "https://api.cline.bot/api/v1",
  apiKey: "YOUR_API_KEY",
})

// Non-streaming
const response = await client.chat.completions.create({
  model: "anthropic/claude-sonnet-4-6",
  messages: [{ role: "user", content: "Explain async/await in one sentence." }],
})
console.log(response.choices[0].message.content)

​
Streaming in Node.js

import OpenAI from "openai"

const client = new OpenAI({
  baseURL: "https://api.cline.bot/api/v1",
  apiKey: "YOUR_API_KEY",
})

const stream = await client.chat.completions.create({
  model: "anthropic/claude-sonnet-4-6",
  messages: [{ role: "user", content: "Write a haiku about TypeScript." }],
  stream: true,
})

for await (const chunk of stream) {
  const content = chunk.choices[0]?.delta?.content
  if (content) {
    process.stdout.write(content)
  }
}
console.log()

​
Using fetch

const response = await fetch("https://api.cline.bot/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "anthropic/claude-sonnet-4-6",
    messages: [{ role: "user", content: "Hello!" }],
    stream: false,
  }),
})

const data = await response.json()
console.log(data.choices[0].message.content)

​
Cline CLI

The Cline CLI is the fastest way to use the Cline API from your terminal. It handles authentication, streaming, and tool execution for you.

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Setup

# Install
npm install -g @anthropic-ai/cline

# Authenticate with a Cline API key
cline auth -p cline -k "YOUR_API_KEY" -m anthropic/claude-sonnet-4-6

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Run Tasks

# Simple prompt
cline "Explain what a REST API is."

# Pipe input
cat README.md | cline "Summarize this document."

# Use a specific model
cline -m google/gemini-2.5-pro "Analyze this codebase."

# YOLO mode for automation
cline -y "Run tests and fix failures."
See the CLI Reference for all commands and options.

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VS Code / JetBrains

The Cline extension handles the API integration for you:
  1. Open the Cline panel in your editor
  2. Select Cline as the provider in the model picker
  3. Sign in with your Cline account
  4. Start chatting or give Cline a task
Your API key is managed automatically. No manual configuration needed. For setup instructions, see Installing Cline and Authorizing with Cline.

Chat Completions

Full endpoint reference with all parameters.

Authentication

API key management and security practices.

Models

Browse available models.

CLI Reference

Complete Cline CLI command reference.