Claude Code SDK

# 運行單一提示並退出（列印模式）
$ claude -p "Write a function to calculate Fibonacci numbers"

# 使用管道提供 stdin
$ echo "Explain this code" | claude -p

# 以 JSON 格式輸出並包含元資料
$ claude -p "Generate a hello world function" --output-format json

# 在接收時串流 JSON 輸出
$ claude -p "Build a React component" --output-format stream-json

import { query, type SDKMessage } from "@anthropic-ai/claude-code";

const messages: SDKMessage[] = [];

for await (const message of query({
  prompt: "Write a haiku about foo.py",
  abortController: new AbortController(),
  options: {
    maxTurns: 3,
  },
})) {
  messages.push(message);
}

console.log(messages);

pip install claude-code-sdk

import anyio
from claude_code_sdk import query, ClaudeCodeOptions, Message

async def main():
    messages: list[Message] = []
    
    async for message in query(
        prompt="Write a haiku about foo.py",
        options=ClaudeCodeOptions(max_turns=3)
    ):
        messages.append(message)
    
    print(messages)

anyio.run(main)

from claude_code_sdk import query, ClaudeCodeOptions
from pathlib import Path

options = ClaudeCodeOptions(
    max_turns=3,
    system_prompt="You are a helpful assistant",
    cwd=Path("/path/to/project"),  # 可以是字串或 Path
    allowed_tools=["Read", "Write", "Bash"],
    permission_mode="acceptEdits"
)

async for message in query(prompt="Hello", options=options):
    print(message)

# 繼續最近的對話
$ claude --continue

# 繼續並提供新的提示
$ claude --continue "Now refactor this for better performance"

# 透過會話 ID 恢復特定對話
$ claude --resume 550e8400-e29b-41d4-a716-446655440000

# 在列印模式（非互動）中恢復
$ claude -p --resume 550e8400-e29b-41d4-a716-446655440000 "Update the tests"

# 在列印模式（非互動）中繼續
$ claude -p --continue "Add error handling"

# 覆蓋系統提示（僅適用於 --print）
$ claude -p "Build a REST API" --system-prompt "You are a senior backend engineer. Focus on security, performance, and maintainability."

# 具有特定要求的系統提示
$ claude -p "Create a database schema" --system-prompt "You are a database architect. Use PostgreSQL best practices and include proper indexing."

# 附加系統提示（僅適用於 --print）
$ claude -p "Build a REST API" --append-system-prompt "After writing code, be sure to code review yourself."

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/files"
      ]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_TOKEN": "your-github-token"
      }
    }
  }
}

# 從配置載入 MCP 伺服器
$ claude -p "List all files in the project" --mcp-config mcp-servers.json

# 重要：必須使用 --allowedTools 明確允許 MCP 工具
# MCP 工具遵循格式：mcp__$serverName__$toolName
$ claude -p "Search for TODO comments" \
  --mcp-config mcp-servers.json \
  --allowedTools "mcp__filesystem__read_file,mcp__filesystem__list_directory"

# 在非互動模式中使用 MCP 工具處理權限提示
$ claude -p "Deploy the application" \
  --mcp-config mcp-servers.json \
  --allowedTools "mcp__permissions__approve" \
  --permission-prompt-tool mcp__permissions__approve

// 允許工具調用
{
  "behavior": "allow",
  "updatedInput": {...}, // 更新的輸入，或只是返回原始輸入
}

// 拒絕工具調用
{
  "behavior": "deny",
  "message": "..." // 解釋為什麼權限被拒絕的人類可讀字串
}

const server = new McpServer({
  name: "Test permission prompt MCP Server",
  version: "0.0.1",
});

server.tool(
  "approval_prompt",
  'Simulate a permission check - approve if the input contains "allow", otherwise deny',
  {
    tool_name: z.string().describe("The tool requesting permission"),
    input: z.object({}).passthrough().describe("The input for the tool"),
  },
  async ({ tool_name, input }) => {
    return {
      content: [
        {
          type: "text",
          text: JSON.stringify(
            JSON.stringify(input).includes("allow")
              ? {
                  behavior: "allow",
                  updatedInput: input,
                }
              : {
                  behavior: "deny",
                  message: "Permission denied by test approval_prompt tool",
                }
          ),
        },
      ],
    };
  }
);

claude -p "..." \
  --permission-prompt-tool mcp__test-server__approval_prompt \
  --mcp-config my-config.json

$ claude -p "Explain file src/components/Header.tsx"
# 輸出：This is a React component showing...

$ claude -p "How does the data layer work?" --output-format json

{
  "type": "result",
  "subtype": "success",
  "total_cost_usd": 0.003,
  "is_error": false,
  "duration_ms": 1234,
  "duration_api_ms": 800,
  "num_turns": 6,
  "result": "The response text here...",
  "session_id": "abc123"
}

$ claude -p "Build an application" --output-format stream-json

type SDKMessage =
  // 助手訊息
  | {
      type: "assistant";
      message: Message; // 來自 Anthropic SDK
      session_id: string;
    }

  // 使用者訊息
  | {
      type: "user";
      message: MessageParam; // 來自 Anthropic SDK
      session_id: string;
    }

  // 作為最後一個訊息發出
  | {
      type: "result";
      subtype: "success";
      duration_ms: float;
      duration_api_ms: float;
      is_error: boolean;
      num_turns: int;
      result: string;
      session_id: string;
      total_cost_usd: float;
    }

  // 當我們達到最大輪次時作為最後一個訊息發出
  | {
      type: "result";
      subtype: "error_max_turns" | "error_during_execution";
      duration_ms: float;
      duration_api_ms: float;
      is_error: boolean;
      num_turns: int;
      session_id: string;
      total_cost_usd: float;
    }

  // 在對話開始時作為第一個訊息發出
  | {
      type: "system";
      subtype: "init";
      apiKeySource: string;
      cwd: string;
      session_id: string;
      tools: string[];
      mcp_servers: {
        name: string;
        status: string;
      }[];
      model: string;
      permissionMode: "default" | "acceptEdits" | "bypassPermissions" | "plan";
    };

$ claude -p "Explain this code"

$ echo "Explain this code" | claude -p

$ echo '{"type":"user","message":{"role":"user","content":[{"type":"text","text":"Explain this code"}]}}' | claude -p --output-format=stream-json --input-format=stream-json --verbose

#!/bin/bash

# 運行 Claude 並檢查退出代碼的簡單函數
run_claude() {
    local prompt="$1"
    local output_format="${2:-text}"

    if claude -p "$prompt" --output-format "$output_format"; then
        echo "Success!"
    else
        echo "Error: Claude failed with exit code $?" >&2
        return 1
    fi
}

# 使用範例
run_claude "Write a Python function to read CSV files"
run_claude "Optimize this database query" "json"

# 透過 Claude 處理檔案
$ cat mycode.py | claude -p "Review this code for bugs"

# 處理多個檔案
$ for file in *.js; do
    echo "Processing $file..."
    claude -p "Add JSDoc comments to this file:" < "$file" > "${file}.documented"
done

# 在管道中使用 Claude
$ grep -l "TODO" *.py | while read file; do
    claude -p "Fix all TODO items in this file" < "$file"
done

# 開始會話並捕獲會話 ID
$ claude -p "Initialize a new project" --output-format json | jq -r '.session_id' > session.txt

# 使用相同會話繼續
$claude -p --resume "$(cat session.txt)" "Add unit tests"