Create Messages (Claude)

curl --request POST \
  --url https://api.mixroute.ai/v1/messages \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --header 'anthropic-version: 2023-06-01' \
  --data '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

message = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
)
print(message.content[0].text)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: 'sk-xxxxxxxxxx',
  baseURL: 'https://api.mixroute.ai'
});

const message = await client.messages.create({
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Briefly explain artificial intelligence' }
  ]
});
console.log(message.content[0].text);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
        'anthropic-version' => '2023-06-01',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'max_tokens' => 1024,
        'messages' => [
            ['role' => 'user', 'content' => 'Briefly explain artificial intelligence']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": []map[string]string{
            {"role": "user", "content": "Briefly explain artificial intelligence"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("anthropic-version", "2023-06-01")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": [{"role": "user", "content": "Briefly explain artificial intelligence"}]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .header("anthropic-version", "2023-06-01")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request['anthropic-version'] = '2023-06-01'
request.body = {
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Briefly explain artificial intelligence' }]
}.to_json

response = http.request(request)
puts response.body

{
  "id": "msg_xxx",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Artificial intelligence is a new technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence..."
    }
  ],
  "model": "claude-opus-4-8",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 25,
    "output_tokens": 100
  }
}

POST

messages

curl --request POST \
  --url https://api.mixroute.ai/v1/messages \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --header 'anthropic-version: 2023-06-01' \
  --data '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

message = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
)
print(message.content[0].text)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: 'sk-xxxxxxxxxx',
  baseURL: 'https://api.mixroute.ai'
});

const message = await client.messages.create({
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Briefly explain artificial intelligence' }
  ]
});
console.log(message.content[0].text);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
        'anthropic-version' => '2023-06-01',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'max_tokens' => 1024,
        'messages' => [
            ['role' => 'user', 'content' => 'Briefly explain artificial intelligence']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": []map[string]string{
            {"role": "user", "content": "Briefly explain artificial intelligence"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("anthropic-version", "2023-06-01")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": [{"role": "user", "content": "Briefly explain artificial intelligence"}]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .header("anthropic-version", "2023-06-01")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request['anthropic-version'] = '2023-06-01'
request.body = {
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Briefly explain artificial intelligence' }]
}.to_json

response = http.request(request)
puts response.body

{
  "id": "msg_xxx",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Artificial intelligence is a new technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence..."
    }
  ],
  "model": "claude-opus-4-8",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 25,
    "output_tokens": 100
  }
}

Introduction

The Messages API provides native Anthropic Claude interface compatibility through MixRoute , allowing direct use of Anthropic SDKs and tools like Claude Code. This interface follows Anthropic’s API specification and provides full Claude model functionality, including Extended Thinking, tool calling, and other advanced features. If you’re using OpenAI-compatible clients (like OpenAI SDK), we recommend using the /v1/chat/completions endpoint instead.

Authentication

Bearer Token, e.g., Bearer sk-xxxxxxxxxx

Request Parameters

string

required

Claude model identifier, e.g., claude-opus-4-8

array

required

List of conversation messages, each containing role (user/assistant) and content

integer

required

Maximum tokens to generate, must be greater than 0

string | array

System prompt, supports string format or array format (for Prompt Caching)

boolean

Enable streaming output

number

Sampling temperature, range 0-1

number

Nucleus sampling parameter, range 0-1

integer

Top-k sampling parameter

array

Custom stop sequences

object

Extended thinking configuration, contains type and budget_tokens

array

List of tool definitions

Basic Examples

Non-Streaming Request
Streaming Request (SSE)
Python Example

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "stream": true,
    "messages": [
      {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

# Non-streaming
message = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
)
print(message.content[0].text)

# Streaming
with client.messages.stream(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
) as stream:
    for text_block in stream.text_stream:
        print(text_block, end="")

Advanced Features

System Prompt

String Format
Array Format

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "system": "You are a professional programming assistant skilled at explaining complex technical concepts.",
    "messages": [
      {"role": "user", "content": "What is recursion?"}
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "system": [
      {
        "type": "text",
        "text": "You are a professional programming assistant skilled at explaining complex technical concepts."
      }
    ],
    "messages": [
      {"role": "user", "content": "What is recursion?"}
    ]
  }'

Extended Thinking

Basic Usage
Python Example

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 16000,
    "thinking": {
      "type": "enabled",
      "budget_tokens": 10000
    },
    "messages": [
      {"role": "user", "content": "Provide a medium difficulty geometry problem and solve it step by step"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

with client.messages.stream(
    model="claude-opus-4-8",
    max_tokens=16000,
    thinking={
        "type": "enabled",
        "budget_tokens": 10000
    },
    messages=[
        {"role": "user", "content": "Provide a medium difficulty geometry problem and solve it step by step"}
    ]
) as stream:
    for event in stream:
        if event.type == "content_block_delta":
            if hasattr(event.delta, "thinking"):
                print(f"[Thinking] {event.delta.thinking}", end="")
            elif hasattr(event.delta, "text"):
                print(event.delta.text, end="")

Tools

Function Tools
Claude Official Web Search Tool

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "tools": [
      {
        "name": "get_weather",
        "description": "Get weather information for a city",
        "input_schema": {
          "type": "object",
          "properties": {
            "city": {
              "type": "string",
              "description": "City name"
            }
          },
          "required": ["city"]
        }
      }
    ],
    "messages": [
      {"role": "user", "content": "What is the weather like in Tokyo?"}
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 4096,
    "tools": [
      {
        "type": "web_search_20250305",
        "name": "web_search",
        "max_uses": 5
      }
    ],
    "messages": [
      {"role": "user", "content": "What are the latest news about artificial intelligence?"}
    ]
  }'

Multimodal Input (Images)

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "image",
            "source": {
              "type": "base64",
              "media_type": "image/jpeg",
              "data": "base64_encoded_image_data"
            }
          },
          {
            "type": "text",
            "text": "Please describe this image"
          }
        ]
      }
    ]
  }'

Prompt Caching

By caching frequently used context content, you can significantly reduce costs and improve response speed. Cached content requires a minimum of 1024 tokens.

System Cache
Messages Cache
Python SDK Example

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "system": [
      {
        "type": "text",
        "text": "You are a professional document analysis assistant. Here is the document content to analyze: [long text content, at least 1024 tokens]",
        "cache_control": {"type": "ephemeral"}
      }
    ],
    "messages": [
      {"role": "user", "content": "Please summarize the main points of the document"}
    ]
  }'

curl -X POST "https://api.mixroute.ai/v1/messages" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Here is the codebase to analyze: [large code content, at least 1024 tokens]",
            "cache_control": {"type": "ephemeral"}
          },
          {
            "type": "text",
            "text": "Please identify potential issues in the code"
          }
        ]
      }
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

# System cache
message = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "You are a professional document analysis assistant. Here is the document content to analyze: [long text content]",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[
        {"role": "user", "content": "Please summarize the main points of the document"}
    ]
)

# Check cache usage
print(f"Cache creation tokens: {message.usage.cache_creation_input_tokens}")
print(f"Cache read tokens: {message.usage.cache_read_input_tokens}")

Response Format

Non-Streaming Response
Streaming Response

{
  "id": "msg_xxx",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Response content..."
    }
  ],
  "model": "claude-opus-4-8",
  "stop_reason": "end_turn",
  "usage": {
    "input_tokens": 25,
    "output_tokens": 100,
    "cache_creation_input_tokens": 0,
    "cache_read_input_tokens": 0
  }
}

event: message_start
data: {"type":"message_start","message":{"id":"msg_xxx","type":"message","role":"assistant","content":[],"model":"claude-opus-4-8"}}

event: content_block_start
data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Response"}}

event: content_block_delta
data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":" content"}}

event: content_block_stop
data: {"type":"content_block_stop","index":0}

event: message_delta
data: {"type":"message_delta","delta":{"stop_reason":"end_turn"},"usage":{"output_tokens":100}}

event: message_stop
data: {"type":"message_stop"}

curl --request POST \
  --url https://api.mixroute.ai/v1/messages \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --header 'anthropic-version: 2023-06-01' \
  --data '{
    "model": "claude-opus-4-8",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
  }'

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

message = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Briefly explain artificial intelligence"}
    ]
)
print(message.content[0].text)

import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
  apiKey: 'sk-xxxxxxxxxx',
  baseURL: 'https://api.mixroute.ai'
});

const message = await client.messages.create({
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [
    { role: 'user', content: 'Briefly explain artificial intelligence' }
  ]
});
console.log(message.content[0].text);

<?php
$client = new GuzzleHttp\Client();
$response = $client->post('https://api.mixroute.ai/v1/messages', [
    'headers' => [
        'Authorization' => 'Bearer sk-xxxxxxxxxx',
        'Content-Type' => 'application/json',
        'anthropic-version' => '2023-06-01',
    ],
    'json' => [
        'model' => 'claude-opus-4-8',
        'max_tokens' => 1024,
        'messages' => [
            ['role' => 'user', 'content' => 'Briefly explain artificial intelligence']
        ]
    ]
]);
echo $response->getBody();

package main

import (
    "bytes"
    "encoding/json"
    "net/http"
)

func main() {
    payload := map[string]interface{}{
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": []map[string]string{
            {"role": "user", "content": "Briefly explain artificial intelligence"},
        },
    }
    body, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages", bytes.NewBuffer(body))
    req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("anthropic-version", "2023-06-01")
    http.DefaultClient.Do(req)
}

import java.net.http.*;
import java.net.URI;

HttpClient client = HttpClient.newHttpClient();
String json = """
    {
        "model": "claude-opus-4-8",
        "max_tokens": 1024,
        "messages": [{"role": "user", "content": "Briefly explain artificial intelligence"}]
    }
    """;
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.mixroute.ai/v1/messages"))
    .header("Authorization", "Bearer sk-xxxxxxxxxx")
    .header("Content-Type", "application/json")
    .header("anthropic-version", "2023-06-01")
    .POST(HttpRequest.BodyPublishers.ofString(json))
    .build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

require 'net/http'
require 'json'

uri = URI('https://api.mixroute.ai/v1/messages')
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true

request = Net::HTTP::Post.new(uri)
request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
request['Content-Type'] = 'application/json'
request['anthropic-version'] = '2023-06-01'
request.body = {
  model: 'claude-opus-4-8',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Briefly explain artificial intelligence' }]
}.to_json

response = http.request(request)
puts response.body

{
  "id": "msg_xxx",
  "type": "message",
  "role": "assistant",
  "content": [
    {
      "type": "text",
      "text": "Artificial intelligence is a new technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence..."
    }
  ],
  "model": "claude-opus-4-8",
  "stop_reason": "end_turn",
  "stop_sequence": null,
  "usage": {
    "input_tokens": 25,
    "output_tokens": 100
  }
}

Create Responses Request (OpenAI)Count Tokens (Claude)

Popular Models

Smart Routing

OpenAI SDK Usage

Text Series

Embedding Series

Image Series

Video Series

Others

Create Messages (Claude)

Introduction

Authentication

Request Parameters

Basic Examples

Advanced Features

System Prompt

Extended Thinking

Tools

Multimodal Input (Images)

Prompt Caching

Response Format

​Introduction

​Authentication

​Request Parameters

​Basic Examples

​Advanced Features

​System Prompt

​Extended Thinking

​Tools

​Multimodal Input (Images)

​Prompt Caching

​Response Format

Introduction

Authentication

Request Parameters

Basic Examples

Advanced Features

System Prompt

Extended Thinking

Tools

Multimodal Input (Images)

Prompt Caching

Response Format