How to integrate Needle MCP with LangChain

This guide walks you through connecting Needle to LangChain using the Composio tool router. By the end, you'll have a working Needle agent that can list all document collections i have, show stats for your 'research' collection, find files in collection uploaded this week through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Needle account through Composio's Needle MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Needle is a RAG (retrieval-augmented generation) toolkit that brings semantic search capabilities to your own data. It lets you build smarter AI agents by giving them context-aware, accurate information retrieval.

16 Tools

Introduction

This guide walks you through connecting Needle to LangChain using the Composio tool router. By the end, you'll have a working Needle agent that can list all document collections i have, show stats for your 'research' collection, find files in collection uploaded this week through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Needle account through Composio's Needle MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

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OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Needle project to Composio
  • Create a Tool Router MCP session for Needle
  • Initialize an MCP client and retrieve Needle tools
  • Build a LangChain agent that can interact with Needle
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Needle MCP server, and what's possible with it?

The Needle MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Needle account. It provides structured and secure access to your semantic search collections, so your agent can perform actions like creating and managing collections, uploading and deleting files, retrieving collection statistics, and listing available data sources on your behalf.

  • Collection management and creation: Easily instruct your agent to create new semantic search collections tailored to your data needs.
  • File listing and retrieval: Have your agent list and retrieve all files within a specific collection, making it simple to view and organize your indexed data.
  • File deletion from collections: Direct your agent to remove unwanted or outdated files from any collection by specifying file IDs for cleanup and maintenance.
  • Collection statistics and insights: Ask your agent to fetch real-time statistics on any collection, including document counts, index size, and timestamps to monitor your data health.
  • Browse all available collections: Let your agent page through and present all your collections, so you can quickly access, search, or manage your data resources.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step10 STEPS
1

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming
2

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • @composio/langchain provides Composio integration for LangChain
  • @langchain/mcp-adapters enables MCP client connections
  • @langchain/core is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models
5

Import dependencies

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv/config import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Needle functionality through MCP
6

Initialize Composio client

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Needle tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding
7

Create a Tool Router session

const session = await composio.create(
    userId as string,
    {
        toolkits: ['needle']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Needle tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Needle tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "needle-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Needle MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Needle tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model
9

Set up interactive chat interface

let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Needle related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

rl.prompt();

rl.on('line', async (userInput: string) => {
    const trimmedInput = userInput.trim();

    if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
        console.log("\nGoodbye!");
        rl.close();
        process.exit(0);
    }

    if (!trimmedInput) {
        rl.prompt();
        return;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
What's happening:
  • We initialize an empty conversationHistory list to maintain context across interactions
  • A readline interface is used to continuously accept user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the invoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully
10

Run the application

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
What's happening:
  • We call the main() function to start the application

Complete Code

Here's the complete code to get you started with Needle and LangChain:

import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['needle']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "needle-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Needle related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    rl.prompt();

    rl.on('line', async (userInput: string) => {
        const trimmedInput = userInput.trim();
        
        if (['exit', 'quit', 'bye'].includes(trimmedInput.toLowerCase())) {
            console.log("\nGoodbye!");
            rl.close();
            process.exit(0);
        }
        
        if (!trimmedInput) {
            rl.prompt();
            return;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});

Conclusion

You've successfully built a LangChain agent that can interact with Needle through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.
TOOLS

Supported Tools

Every Needle action and event your agent gets out of the box.

Add files to a collection

Tool to add files to a collection by providing file URLs.

Add Files to Local Connector

Tool to add files to a local connector by providing file metadata.

Create Collection

Tool to create a new collection.

Create Local Connector

Tool to create a local connector that monitors specified folders on a device.

Delete files from a collection

Tool to delete files from a specific collection by providing file IDs.

Delete files from local connector

Tool to delete files from a local connector by filename or file IDs.

Get Collection

Tool to retrieve details for a specific collection by its ID.

Get collection stats

Tool to retrieve statistics for a specific collection by its ID.

Get File Download URL

Tool to get a short-lived signed private download URL for a Needle file.

Get File Upload URL

Tool to get signed URLs for uploading local files to Needle.

Get local connector

Tool to retrieve details of a local connector by its ID.

List Collection Files

Tool to list all files within a specific collection by its ID.

List Collections

Tool to list collections.

List Connectors

Tool to list connectors.

List Local Connectors

Tool to list local connectors.

Search Collection

Tool to perform semantic search within a specific Needle collection and return ranked results with source references.

FRAMEWORKS

How to build Needle MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Needle MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Needle MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Needle MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Needle MCP with Claude Cowork

Codex logo

Codex

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OpenClaw logo

OpenClaw

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Hermes logo

Hermes

Use Needle MCP with Hermes

CLI logo

CLI

Use Needle MCP with CLI

Google ADK logo

Google ADK

Use Needle MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Needle MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Needle MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Needle MCP with LlamaIndex

CrewAI logo

CrewAI

Use Needle MCP with CrewAI

FAQ

Frequently asked questions

With a standalone Needle MCP server, the agents and LLMs can only access a fixed set of Needle tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Needle and many other apps based on the task at hand, all through a single MCP endpoint.

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Needle tools.

Yes, absolutely. You can configure which Needle scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Needle data and credentials are handled as safely as possible.

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