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The @langchain/anthropic package provides LangChain-compatible wrappers for Anthropic’s built-in tools. These tools can be bound to ChatAnthropic using bindTools() or createAgent.
The memory tool (memory_20250818) enables Claude to store and retrieve information across conversations through a memory file directory. Claude can create, read, update, and delete files that persist between sessions, allowing it to build knowledge over time without keeping everything in the context window.
import { ChatAnthropic, tools } from "@langchain/anthropic";// Create a simple in-memory file store (or use your own persistence layer)const files = new Map<string, string>();const memory = tools.memory_20250818({ execute: async (command) => { switch (command.command) { case "view": if (!command.path || command.path === "/") { return Array.from(files.keys()).join("\n") || "Directory is empty."; } return ( files.get(command.path) ?? `Error: File not found: ${command.path}` ); case "create": files.set(command.path!, command.file_text ?? ""); return `Successfully created file: ${command.path}`; case "str_replace": const content = files.get(command.path!); if (content && command.old_str) { files.set( command.path!, content.replace(command.old_str, command.new_str ?? "") ); } return `Successfully replaced text in: ${command.path}`; case "delete": files.delete(command.path!); return `Successfully deleted: ${command.path}`; // Handle other commands: insert, rename default: return `Unknown command`; } },});const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});const llmWithMemory = llm.bindTools([memory]);const response = await llmWithMemory.invoke( "Remember that my favorite programming language is TypeScript");
The web search tool (webSearch_20250305) gives Claude direct access to real-time web content, allowing it to answer questions with up-to-date information beyond its knowledge cutoff. Claude automatically cites sources from search results as part of its answer.
import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});// Basic usageconst response = await llm.invoke("What is the weather in NYC?", { tools: [tools.webSearch_20250305()],});
The web search tool supports several configuration options:
const response = await llm.invoke("Latest news about AI?", { tools: [ tools.webSearch_20250305({ // Maximum number of times the tool can be used in the API request maxUses: 5, // Only include results from these domains allowedDomains: ["reuters.com", "bbc.com"], // Or block specific domains (cannot be used with allowedDomains) // blockedDomains: ["example.com"], // Provide user location for more relevant results userLocation: { type: "approximate", city: "San Francisco", region: "California", country: "US", timezone: "America/Los_Angeles", }, }), ],});
The web fetch tool (webFetch_20250910) allows Claude to retrieve full content from specified web pages and PDF documents. Claude can only fetch URLs that have been explicitly provided by the user or that come from previous web search or web fetch results.
⚠️ Security Warning: Enabling the web fetch tool in environments where Claude processes untrusted input alongside sensitive data poses data exfiltration risks. We recommend only using this tool in trusted environments or when handling non-sensitive data.
import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});// Basic usage - fetch content from a URLconst response = await llm.invoke( "Please analyze the content at https://example.com/article", { tools: [tools.webFetch_20250910()] });
The web fetch tool supports several configuration options:
const response = await llm.invoke( "Summarize this research paper: https://arxiv.org/abs/2024.12345", { tools: [ tools.webFetch_20250910({ // Maximum number of times the tool can be used in the API request maxUses: 5, // Only fetch from these domains allowedDomains: ["arxiv.org", "example.com"], // Or block specific domains (cannot be used with allowedDomains) // blockedDomains: ["example.com"], // Enable citations for fetched content (optional, unlike web search) citations: { enabled: true }, // Maximum content length in tokens (helps control token usage) maxContentTokens: 50000, }), ], });
You can combine web fetch with web search for comprehensive information gathering:
import { tools } from "@langchain/anthropic";const response = await llm.invoke( "Find recent articles about quantum computing and analyze the most relevant one", { tools: [ tools.webSearch_20250305({ maxUses: 3 }), tools.webFetch_20250910({ maxUses: 5, citations: { enabled: true } }), ], });
The tool search tools enable Claude to work with hundreds or thousands of tools by dynamically discovering and loading them on-demand. This is useful when you have a large number of tools but don’t want to load them all into the context window at once.There are two variants:
toolSearchRegex_20251119 - Claude constructs regex patterns (using Python’s re.search() syntax) to search for tools
toolSearchBM25_20251119 - Claude uses natural language queries to search for tools using the BM25 algorithm
import { ChatAnthropic, tools } from "@langchain/anthropic";import { tool } from "langchain";import { z } from "zod";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});// Create tools with defer_loading to make them discoverable via searchconst getWeather = tool( async (input: { location: string }) => { return `Weather in ${input.location}: Sunny, 72°F`; }, { name: "get_weather", description: "Get the weather at a specific location", schema: z.object({ location: z.string(), }), extras: { defer_loading: true }, });const getNews = tool( async (input: { topic: string }) => { return `Latest news about ${input.topic}...`; }, { name: "get_news", description: "Get the latest news about a topic", schema: z.object({ topic: z.string(), }), extras: { defer_loading: true }, });// Claude will search and discover tools as neededconst response = await llm.invoke("What is the weather in San Francisco?", { tools: [tools.toolSearchRegex_20251119(), getWeather, getNews],});
Using the BM25 variant for natural language search:
import { tools } from "@langchain/anthropic";const response = await llm.invoke("What is the weather in San Francisco?", { tools: [tools.toolSearchBM25_20251119(), getWeather, getNews],});
The text editor tool (textEditor_20250728) enables Claude to view and modify text files, helping debug, fix, and improve code or other text documents. Claude can directly interact with files, providing hands-on assistance rather than just suggesting changes.Available commands:
view - Examine file contents or list directory contents
str_replace - Replace specific text in a file
create - Create a new file with specified content
insert - Insert text at a specific line number
import fs from "node:fs";import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});const textEditor = tools.textEditor_20250728({ async execute(args) { switch (args.command) { case "view": const content = fs.readFileSync(args.path, "utf-8"); // Return with line numbers for Claude to reference return content .split("\n") .map((line, i) => `${i + 1}: ${line}`) .join("\n"); case "str_replace": let fileContent = fs.readFileSync(args.path, "utf-8"); fileContent = fileContent.replace(args.old_str, args.new_str); fs.writeFileSync(args.path, fileContent); return "Successfully replaced text."; case "create": fs.writeFileSync(args.path, args.file_text); return `Successfully created file: ${args.path}`; case "insert": const lines = fs.readFileSync(args.path, "utf-8").split("\n"); lines.splice(args.insert_line, 0, args.new_str); fs.writeFileSync(args.path, lines.join("\n")); return `Successfully inserted text at line ${args.insert_line}`; default: return "Unknown command"; } }, // Optional: limit file content length when viewing maxCharacters: 10000,});const llmWithEditor = llm.bindTools([textEditor]);const response = await llmWithEditor.invoke( "There's a syntax error in my primes.py file. Can you help me fix it?");
The computer use tools enable Claude to interact with desktop environments through screenshot capture, mouse control, and keyboard input for autonomous desktop interaction.
⚠️ Security Warning: Computer use is a beta feature with unique risks. Use a dedicated virtual machine or container with minimal privileges. Avoid giving access to sensitive data.
There are two variants:
computer_20251124 - For Claude Opus 4.5 (includes zoom capability)
computer_20250124 - For Claude 4 and Claude 3.7 models
Available actions:
screenshot - Capture the current screen
left_click, right_click, middle_click - Mouse clicks at coordinates
double_click, triple_click - Multi-click actions
left_click_drag - Click and drag operations
left_mouse_down, left_mouse_up - Granular mouse control
scroll - Scroll the screen
type - Type text
key - Press keyboard keys/shortcuts
mouse_move - Move the cursor
hold_key - Hold a key while performing other actions
wait - Wait for a specified duration
zoom - View specific screen regions at full resolution (Claude Opus 4.5 only)
import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});const computer = tools.computer_20250124({ // Required: specify display dimensions displayWidthPx: 1024, displayHeightPx: 768, // Optional: X11 display number displayNumber: 1, execute: async (action) => { switch (action.action) { case "screenshot": // Capture and return base64-encoded screenshot // ... case "left_click": // Click at the specified coordinates // ... // ... } },});const llmWithComputer = llm.bindTools([computer]);const response = await llmWithComputer.invoke( "Save a picture of a cat to my desktop.");
For Claude Opus 4.5 with zoom support:
import { tools } from "@langchain/anthropic";const computer = tools.computer_20251124({ displayWidthPx: 1920, displayHeightPx: 1080, // Enable zoom for detailed screen region inspection enableZoom: true, execute: async (action) => { // Handle actions including "zoom" for Claude Opus 4.5 // ... },});
The code execution tool (codeExecution_20250825) allows Claude to run Bash commands and manipulate files in a secure, sandboxed environment. Claude can analyze data, create visualizations, perform calculations, and process files.When this tool is provided, Claude automatically gains access to:
Bash commands - Execute shell commands for system operations
File operations - Create, view, and edit files directly
import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});// Basic usage - calculations and data analysisconst response = await llm.invoke( "Calculate the mean and standard deviation of [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]", { tools: [tools.codeExecution_20250825()] });// File operations and visualizationconst response2 = await llm.invoke( "Create a matplotlib visualization of sales data and save it as chart.png", { tools: [tools.codeExecution_20250825()] });
Container reuse for multi-step workflows:
// First request - creates a containerconst response1 = await llm.invoke("Write a random number to /tmp/number.txt", { tools: [tools.codeExecution_20250825()],});// Extract container ID from response for reuseconst containerId = response1.response_metadata?.container?.id;// Second request - reuse container to access the fileconst response2 = await llm.invoke( "Read /tmp/number.txt and calculate its square", { tools: [tools.codeExecution_20250825()], container: containerId, });
The bash tool (bash_20250124) enables shell command execution in a persistent bash session. Unlike the sandboxed code execution tool, this tool requires you to provide your own execution environment.
⚠️ Security Warning: The bash tool provides direct system access. Implement safety measures such as running in isolated environments (Docker/VM), command filtering, and resource limits.
The bash tool provides:
Persistent bash session - Maintains state between commands
Shell command execution - Run any shell command
Environment access - Access to environment variables and working directory
Command chaining - Support for pipes, redirects, and scripting
Available commands:
Execute a command: { command: "ls -la" }
Restart the session: { restart: true }
import { ChatAnthropic, tools } from "@langchain/anthropic";import { execSync } from "child_process";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});const bash = tools.bash_20250124({ execute: async (args) => { if (args.restart) { // Reset session state return "Bash session restarted"; } try { const output = execSync(args.command, { encoding: "utf-8", timeout: 30000, }); return output; } catch (error) { return `Error: ${(error as Error).message}`; } },});const llmWithBash = llm.bindTools([bash]);const response = await llmWithBash.invoke( "List all Python files in the current directory");// Process tool calls and execute commandsconsole.log(response.tool_calls?.[0].name); // "bash"console.log(response.tool_calls?.[0].args.command); // "ls -la *.py"
The MCP toolset (mcpToolset_20251120) enables Claude to connect to remote MCP (Model Context Protocol) servers directly from the Messages API without implementing a separate MCP client. This allows Claude to use tools provided by MCP servers.Key features:
Direct API integration - Connect to MCP servers without implementing an MCP client
Tool calling support - Access MCP tools through the Messages API
Flexible tool configuration - Enable all tools, allowlist specific tools, or denylist unwanted tools
Per-tool configuration - Configure individual tools with custom settings
OAuth authentication - Support for OAuth Bearer tokens for authenticated servers
Multiple servers - Connect to multiple MCP servers in a single request
import { ChatAnthropic, tools } from "@langchain/anthropic";const llm = new ChatAnthropic({ model: "claude-sonnet-4-6",});// Basic usage - enable all tools from an MCP serverconst response = await llm.invoke("What tools do you have available?", { mcp_servers: [ { type: "url", url: "https://example-server.modelcontextprotocol.io/sse", name: "example-mcp", authorization_token: "YOUR_TOKEN", }, ], tools: [tools.mcpToolset_20251120({ serverName: "example-mcp" })],});