How to integrate Excel MCP with LlamaIndex

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Introduction

This guide walks you through connecting Excel to LlamaIndex 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can add sales data row to q2 table, create bar chart from revenue column, share this workbook with my manager, clear outdated entries from worksheet range through natural language commands.

This guide will help you understand how to give your LlamaIndex 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.

TL;DR

Here's what you'll learn:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Excel
  • Connect LlamaIndex to the Excel MCP server
  • Build a Excel-powered agent using LlamaIndex
  • Interact with Excel through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built for async/await patterns

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.

Supported Tools & Triggers

Tools
Add ChartAdd a chart to a worksheet using microsoft graph api.
Add SharePoint WorksheetAdd a new worksheet to a sharepoint excel workbook using microsoft graph sites api.
Add TableCreate a table in a workbook using microsoft graph api.
Add Table ColumnAdd a column to a table using microsoft graph api.
Add Table RowAdd a row to a table using microsoft graph api.
Add Workbook PermissionTool to grant access to a workbook via invite.
Add WorksheetAdd a new worksheet to an excel workbook using microsoft graph api.
Apply Table FilterApply a filter to a table column using microsoft graph api.
Apply Table SortApply a sort to a table using microsoft graph api.
Clear RangeTool to clear values, formats, or contents in a specified worksheet range.
Clear Table FilterClear a filter from a table column using microsoft graph api.
Close Excel SessionTool to close an existing excel workbook session.
Convert Table To RangeConvert a table to a range using microsoft graph api.
Create WorkbookTool to create a new workbook file at a specified drive path.
Delete Table ColumnDelete a column from a table using microsoft graph api.
Delete Table RowDelete a row from a table using microsoft graph api.
Delete WorksheetTool to delete a worksheet from the workbook.
Get Chart AxisTool to retrieve a specific axis from a chart.
Get Chart Data LabelsTool to retrieve the data labels object of a chart.
Get Chart LegendTool to retrieve the legend object of a chart.
Get RangeGet a range from a worksheet using microsoft graph api.
Create Excel SessionCreate a session for an excel workbook using microsoft graph api.
Get SharePoint RangeGet a range from a worksheet in sharepoint using microsoft graph sites api.
Get SharePoint WorksheetGet a worksheet by name or id from a sharepoint excel workbook using microsoft graph sites api.
Get Table ColumnTool to retrieve a specific column from a workbook table.
Get workbookTool to retrieve the properties and relationships of a workbook.
Get WorksheetGet a worksheet by name or id from an excel workbook using microsoft graph api.
Insert RangeTool to insert a new cell range into a worksheet, shifting existing cells down or right.
List ChartsList charts in a worksheet using microsoft graph api.
List Chart SeriesTool to list all data series in a chart.
List CommentsTool to list comments in an excel workbook.
List Drive FilesList files and folders in a drive root or specified path.
List Named ItemsList named items in a workbook using microsoft graph api.
List SharePoint TablesList tables in a sharepoint worksheet using microsoft graph sites api.
List SharePoint WorksheetsList worksheets in an excel workbook stored in sharepoint using microsoft graph sites api.
List Table ColumnsList columns in a table using microsoft graph api.
List Table RowsList rows in a table using microsoft graph api.
List TablesList tables in a worksheet using microsoft graph api.
List Workbook PermissionsTool to list permissions set on the workbook file.
List WorksheetsList worksheets in an excel workbook using microsoft graph api.
Merge CellsMerge cells in a worksheet range using microsoft graph api.
Protect WorksheetTool to protect a worksheet using optional protection options.
Sort RangeSort a range in a worksheet using microsoft graph api.
Update ChartUpdate a chart in a worksheet using microsoft graph api.
Update Chart LegendTool to update formatting or position of a chart legend.
Update RangeUpdate a range in a worksheet using microsoft graph api.
Update SharePoint RangeUpdate a range in a sharepoint worksheet using microsoft graph sites api.
Update TableUpdate a table in a workbook using microsoft graph api.
Update WorksheetUpdate worksheet properties (name, position) in an excel workbook using microsoft graph api.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Excel account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Excel

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID

Installing dependencies

pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv

Create a new Python project and install the necessary dependencies:

  • composio-llamaindex: Composio's LlamaIndex integration
  • llama-index: Core LlamaIndex framework
  • llama-index-llms-openai: OpenAI LLM integration
  • llama-index-tools-mcp: MCP client for LlamaIndex
  • python-dotenv: Environment variable management

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Excel access

Import modules

import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

Create a new file called excel_llamaindex_agent.py and import the required modules:

Key imports:

  • asyncio: For async/await support
  • Composio: Main client for Composio services
  • LlamaIndexProvider: Adapts Composio tools for LlamaIndex
  • ReActAgent: LlamaIndex's reasoning and action agent
  • BasicMCPClient: Connects to MCP endpoints
  • McpToolSpec: Converts MCP tools to LlamaIndex format

Load environment variables and initialize Composio

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

Create a Tool Router session and build the agent function

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["excel"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Excel actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Excel actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, excel)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Excel tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.

Create an interactive chat loop

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

What's happening here:

  • We're creating a direct terminal interface to chat with your Excel database
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are displayed in a clear, readable format

Define the main entry point

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Excel

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Excel, then start asking questions.

Complete Code

Here's the complete code to get you started with Excel and LlamaIndex:

import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["excel"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Excel actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Excel actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")

Conclusion

You've successfully connected Excel to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Excel tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

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CrewAI

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FAQ

What are the differences in Tool Router MCP and Excel MCP?

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.

Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex 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.

Can I manage the permissions and scopes for Excel while using Tool Router?

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.

How safe is my data with Composio Tool Router?

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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Altera
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Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
ASU
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

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