How to integrate Excel MCP with LangChain

This guide walks you through connecting Excel to LangChain using the Composio tool router. By the end, you'll have a working Excel agent that can add sales data row to q2 table, create bar chart from revenue column, share this workbook with your manager through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Excel account through Composio's Excel MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.

54 Tools

Introduction

This guide walks you through connecting Excel to LangChain using the Composio tool router. By the end, you'll have a working Excel agent that can add sales data row to q2 table, create bar chart from revenue column, share this workbook with your manager through natural language commands.

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

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

Also integrate Excel with

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TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Excel project to Composio
  • Create a Tool Router MCP session for Excel
  • Initialize an MCP client and retrieve Excel tools
  • Build a LangChain agent that can interact with Excel
  • 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 Excel MCP server, and what's possible with it?

The Excel MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Excel account. It provides structured and secure access to your spreadsheets, so your agent can perform actions like adding data, creating tables, managing worksheets, generating charts, and sharing workbooks on your behalf.

  • Automated data entry and updates: Let your agent add rows, columns, or clear specific ranges in any worksheet—keeping your data fresh, organized, and accurate.
  • Effortless table and worksheet management: Direct your agent to create tables, add new worksheets, or organize data structures for seamless tracking and reporting.
  • Dynamic chart generation: Have your agent visualize your data instantly by adding charts to any worksheet for quick insights and analysis.
  • Advanced filtering and sorting: Ask your agent to apply filters or custom sorts to tables, making it easy to focus on what matters most in your datasets.
  • Secure sharing and permission control: Empower your agent to grant access or update permissions on workbooks, ensuring your team can collaborate safely and efficiently.

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 Excel 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 Excel 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: ['excel']
    }
);

const url = session.mcp.url;
What's happening:
  • We're creating a Tool Router session that gives your agent access to Excel 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 Excel tools as needed
8

Configure the agent with the MCP URL

const client = new MultiServerMCPClient({
    "excel-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 Excel MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • getTools() retrieves all available Excel 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 Excel 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 Excel 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: ['excel']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "excel-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 Excel 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 Excel 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 Excel action and event your agent gets out of the box.

Add Chart

Add a chart to a worksheet using Microsoft Graph API.

Add SharePoint Worksheet

Add a new worksheet to a SharePoint Excel workbook using Microsoft Graph Sites API.

Add Table

Create a new table in a worksheet using the Microsoft Graph API.

Add Table Column

Add a column to a table using Microsoft Graph API.

Add Table Row

Add a row to a table using Microsoft Graph API.

Add Workbook Permission

Tool to grant access to a workbook via invite.

Add Worksheet

Add a new worksheet to an Excel workbook using Microsoft Graph API.

Apply Table Filter

Apply a filter to a table column using Microsoft Graph API.

Apply Table Sort

Apply a sort to a table using Microsoft Graph API.

Clear Range

Tool to clear values, formats, or contents in a specified worksheet range.

Clear Table Filter

Clear a filter from a table column using Microsoft Graph API.

Close Excel Session

Tool to close an existing Excel workbook session.

Convert Table To Range

Convert a table to a range using Microsoft Graph API.

Create Workbook

Tool to create a new Excel workbook file at a specified drive path.

Delete Table Column

Delete a column from a table using Microsoft Graph API.

Delete Table Row

Delete a row from a table using Microsoft Graph API.

Delete Worksheet

Tool to delete a worksheet from the workbook.

Export Workbook to PDF

Tool to export an Excel workbook to PDF via Microsoft Graph's format conversion.

Get Chart Axis

Tool to retrieve a specific axis from a chart.

Get Chart Data Labels

Tool to retrieve the data labels object of a chart.

Get Chart Legend

Tool to retrieve the legend object of a chart.

Get Range

Get a range from a worksheet using Microsoft Graph API.

Create Excel Session

Create a session for an Excel workbook using Microsoft Graph API.

Get SharePoint Range

Get a range from a worksheet in SharePoint using Microsoft Graph Sites API.

Get SharePoint Worksheet

Get a worksheet by name or ID from a SharePoint Excel workbook using Microsoft Graph Sites API.

Get table column

Tool to retrieve a specific column from a workbook table.

Get workbook

Tool to retrieve the properties and relationships of a workbook.

Get Worksheet

Get a worksheet by name or ID from an Excel workbook using Microsoft Graph API.

Get Worksheet Used Range

Tool to retrieve a worksheet's used range (active data region) without specifying a fixed range address.

Insert Range

Tool to insert a new cell range into a worksheet, shifting existing cells down or right.

List Charts

List charts in a worksheet using Microsoft Graph API.

List Chart Series

Tool to list all data series in a chart.

List Comments

Tool to list comments in an Excel workbook.

List Drive Item Children

Tool to list immediate children (files/folders) of a folder DriveItem using driveId and itemId.

List Drive Files

List files and folders in a drive root or specified path.

List Named Items

List named items in a workbook using Microsoft Graph API.

List SharePoint Tables

List tables in a SharePoint worksheet using Microsoft Graph Sites API.

List SharePoint Worksheets

List worksheets in an Excel workbook stored in SharePoint using Microsoft Graph Sites API.

List Table Columns

List columns in a table using Microsoft Graph API.

List Table Rows

List rows in a table using Microsoft Graph API.

List Tables

List tables in a worksheet using Microsoft Graph API.

List Workbook Permissions

Tool to list permissions set on the workbook file.

List Worksheets

List worksheets in an Excel workbook using Microsoft Graph API.

Merge Cells

Merge cells in a worksheet range using Microsoft Graph API.

Protect Worksheet

Tool to protect a worksheet using optional protection options.

Search Drive Files

Tool to search OneDrive drive items by query to discover Excel workbook IDs.

Sort Range

Sort a range in a worksheet using Microsoft Graph API.

Update Chart

Update a chart in a worksheet using Microsoft Graph API.

Update Chart Legend

Tool to update formatting or position of a chart legend.

Update Range

Update a range in a worksheet using Microsoft Graph API.

Update SharePoint Range

Update a range in a SharePoint worksheet using Microsoft Graph Sites API.

Update Table

Update a table in a workbook using Microsoft Graph API.

Update Worksheet

Update worksheet properties (name, position) in an Excel workbook using Microsoft Graph API.

Upload Workbook from URL

Tool to upload an external Excel file from a URL into OneDrive/SharePoint.

FRAMEWORKS

How to build Excel MCP Agent with another framework

ChatGPT logo

ChatGPT

Use Excel MCP with ChatGPT

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Excel MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Excel MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Excel MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Excel MCP with Claude Cowork

Codex logo

Codex

Use Excel MCP with Codex

Cursor logo

Cursor

Use Excel MCP with Cursor

OpenClaw logo

OpenClaw

Use Excel MCP with OpenClaw

Hermes logo

Hermes

Use Excel MCP with Hermes

CLI logo

CLI

Use Excel MCP with CLI

Google ADK logo

Google ADK

Use Excel MCP with Google ADK

Vercel AI SDK logo

Vercel AI SDK

Use Excel MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Excel MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Excel MCP with LlamaIndex

CrewAI logo

CrewAI

Use Excel MCP with CrewAI

OpenCode logo

OpenCode

Use Excel MCP with OpenCode

VS Code logo

VS Code

Use Excel MCP with VS Code

FAQ

Frequently asked questions

With a standalone Excel MCP server, the agents and LLMs can only access a fixed set of Excel tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Excel 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 Excel tools.

Yes, absolutely. You can configure which Excel 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 Excel data and credentials are handled as safely as possible.

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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

Abhi Arya
Abhi Arya
Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

Nirman Dave
Nirman Dave
CEO, Zams

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

Ryan Yu
Ryan Yu
Founder, Extra Thursday

Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

Tomisin Jenrola
Tomisin Jenrola
Founder & CEO, SwarmZero

With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

Jerome Leclanche
Jerome Leclanche
Co-Founder, Ingram Technologies