How to integrate Google Sheets MCP with LlamaIndex

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Introduction

This guide walks you through connecting Google Sheets to LlamaIndex using the Composio tool router. By the end, you'll have a working Google Sheets agent that can add a new sheet named 'q3 sales', update all rows where status is 'pending', create a pie chart of expenses by category, clear values in the 'drafts' worksheet through natural language commands.

This guide will help you understand how to give your LlamaIndex agent real control over a Google Sheets account through Composio's Google Sheets 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 Google Sheets
  • Connect LlamaIndex to the Google Sheets MCP server
  • Build a Google Sheets-powered agent using LlamaIndex
  • Interact with Google Sheets 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 Google Sheets MCP server, and what's possible with it?

The Google Sheets MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Google Sheets account. It provides structured and secure access to your spreadsheets, so your agent can perform actions like creating new sheets, updating data, generating charts, and automating spreadsheet workflows on your behalf.

  • Spreadsheet creation and management: Instantly create new Google Sheets and add new worksheets (tabs) to existing spreadsheets whenever you need extra space or organization.
  • Bulk data reading and updating: Retrieve specific data ranges, aggregate column data, or update multiple rows and cells at once—perfect for reporting or syncing external data.
  • Automated chart generation: Direct your agent to build charts from selected data, making visualization and analysis faster and easier right inside your sheets.
  • Smart filtering and data cleanup: Have the agent clear filters, remove cell contents, or append rows and columns to keep your sheets tidy and up to date.
  • Dynamic data manipulation: Use advanced features like batch updates with data filters and aggregate operations to transform, filter, or summarize spreadsheet data efficiently.

Supported Tools & Triggers

Tools
Triggers
Add Sheet to SpreadsheetAdds a new sheet (worksheet) to a spreadsheet.
Aggregate Column DataSearches for rows where a specific column matches a value and performs mathematical operations on data from another column.
Append DimensionTool to append new rows or columns to a sheet, increasing its size.
Batch get spreadsheetRetrieves data from specified cell ranges in a google spreadsheet; ensure the spreadsheet has at least one worksheet and any explicitly referenced sheet names in ranges exist.
Batch update spreadsheetUpdates a specified range in a google sheet with given values, or appends them as new rows if `first cell location` is omitted; ensure the target sheet exists and the spreadsheet contains at least one worksheet.
Batch Update Values by Data FilterTool to update values in ranges matching data filters.
Clear Basic FilterTool to clear the basic filter from a sheet.
Clear spreadsheet valuesClears cell content (preserving formatting and notes) from a specified a1 notation range in a google spreadsheet; the range must correspond to an existing sheet and cells.
Create Chart in Google SheetsCreate a chart in a google sheets spreadsheet using the specified data range and chart type.
Create a Google SheetCreates a new google spreadsheet in google drive using the provided title.
Create spreadsheet columnCreates a new column in a google spreadsheet, requiring a valid `spreadsheet id` and an existing `sheet id`; an out-of-bounds `insert index` may append/prepend the column.
Create spreadsheet rowInserts a new, empty row into a specified sheet of a google spreadsheet at a given index, optionally inheriting formatting from the row above.
Delete Dimension (Rows/Columns)Tool to delete specified rows or columns from a sheet in a google spreadsheet.
Delete SheetTool to delete a sheet (worksheet) from a spreadsheet.
Execute SQL on SpreadsheetExecute sql queries against google sheets tables.
Find worksheet by titleFinds a worksheet by its exact, case-sensitive title within a google spreadsheet; returns a boolean indicating if found and the complete metadata of the entire spreadsheet, regardless of whether the target worksheet is found.
Format cellApplies text and background cell formatting to a specified range in a google sheets worksheet.
Get sheet namesLists all worksheet names from a specified google spreadsheet (which must exist), useful for discovering sheets before further operations.
Get Spreadsheet by Data FilterReturns the spreadsheet at the given id, filtered by the specified data filters.
Get spreadsheet infoRetrieves comprehensive metadata for a google spreadsheet using its id, excluding cell data.
Get Table SchemaThis action is used to get the schema of a table in a google spreadsheet, call this action to get the schema of a table in a spreadsheet before you query the table.
Insert Dimension in Google SheetTool to insert new rows or columns into a sheet at a specified location.
List Tables in SpreadsheetThis action is used to list all tables in a google spreadsheet, call this action to get the list of tables in a spreadsheet.
Look up spreadsheet rowFinds the first row in a google spreadsheet where a cell's entire content exactly matches the query string, searching within a specified a1 notation range or the first sheet by default.
Query Spreadsheet TableThis action is used to query a table in a google spreadsheet, call this action to query a table in a spreadsheet.
Search Developer MetadataTool to search for developer metadata in a spreadsheet.
Search SpreadsheetsSearch for google spreadsheets using various filters including name, content, date ranges, and more.
Set Basic FilterTool to set a basic filter on a sheet in a google spreadsheet.
Create sheet from JSONCreates a new google spreadsheet and populates its first worksheet from `sheet json`, which must be non-empty as its first item's keys establish the headers.
Copy Sheet to Another SpreadsheetTool to copy a single sheet from a spreadsheet to another spreadsheet.
Append Values to SpreadsheetTool to append values to a spreadsheet.
Batch Clear Spreadsheet ValuesTool to clear one or more ranges of values from a spreadsheet.
Batch Clear Values By Data FilterClears one or more ranges of values from a spreadsheet using data filters.
Batch Get Spreadsheet Values by Data FilterTool to return one or more ranges of values from a spreadsheet that match the specified data filters.
Update Sheet PropertiesTool to update properties of a sheet (worksheet) within a google spreadsheet, such as its title, index, visibility, tab color, or grid properties.
Update Spreadsheet PropertiesTool to update properties of a spreadsheet, such as its title, locale, or auto-recalculation settings.

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 Google Sheets account and project
  • Basic familiarity with async Python/Typescript

Getting API Keys for OpenAI, Composio, and Google Sheets

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 Google Sheets 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 google sheets_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=["googlesheets"],
    )

    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 Google Sheets actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Google Sheets 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, google sheets)
  • 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 Google Sheets 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 Google Sheets 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 Google Sheets

Run the agent

npx ts-node llamaindex-agent.ts

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

Complete Code

Here's the complete code to get you started with Google Sheets 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=["googlesheets"],
    )

    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 Google Sheets actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Google Sheets 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 Google Sheets to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Google Sheets 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.

How to build Google Sheets MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Google Sheets MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Google Sheets MCP with Claude Agent SDK

Google ADK

Google ADK

Use Google Sheets MCP with Google ADK

LangChain

LangChain

Use Google Sheets MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Google Sheets MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Google Sheets MCP with Mastra AI

CrewAI

CrewAI

Use Google Sheets MCP with CrewAI

FAQ

What are the differences in Tool Router MCP and Google Sheets MCP?

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

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

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

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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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