LangChain (TypeScript)
A TypeScript client that lets you use any MCP server tools directly within LangChain.js workflows and agents.
Enable LangChain workflows for your MCP client.
What it does
- Connect MCP servers to LangChain.js agents
- Convert MCP tools to LangChain-compatible format
- Execute MCP server operations from TypeScript
- Handle long-running operations with progress updates
- Sample from LLMs using MCP's sampling feature
- Access and manipulate MCP resources
Best for
About LangChain (TypeScript)
LangChain (TypeScript) is a community-built MCP server published by isaacwasserman that provides AI assistants with tools and capabilities via the Model Context Protocol. Enable LangChain workflows for your MCP client using LangChain (TypeScript). Learn more with resources from LangChain Gi It is categorized under ai ml, developer tools. This server exposes 11 tools that AI clients can invoke during conversations and coding sessions.
How to install
You can install LangChain (TypeScript) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
LangChain (TypeScript) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Tools (11)
Echoes back the input
Adds two numbers
Demonstrates a long running operation with progress updates
Prints all environment variables, helpful for debugging MCP server configuration
Samples from an LLM using MCP's sampling feature
mcp-langchain-ts-client
A LangChain.js client for Model Context Protocol.
This is a port of rectalogic/langchain-mcp to the JS/TS LangChain and MCP APIs.
Installation
npm install mcp-langchain-ts-client
Usage
const serverParams = {
command: "npx",
args: [
"-y",
"@modelcontextprotocol/server-everything"
]
}
// Initialize the toolkit
const toolkit = new MCPToolkit(serverParams);
await toolkit.initialize();
// Extract LangChain.js compatible tools
const tools = toolkit.tools;
// Use the tools
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { ChatAnthropic } from "@langchain/anthropic";
const llm = new ChatAnthropic({ model: 'claude-3-5-sonnet-20241022' });
const agent = createReactAgent({ llm, tools });
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