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How to integrate Grist MCP with Pydantic AI

Connect Pydantic AI to Grist MCP. Add new sales data to q2 table, create a document for project planning, and more using natural language, with authentication handled for you.

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Grist is a relational spreadsheet platform combining spreadsheet flexibility with database power. It helps you build custom applications tailored to your unique data needs.

30 Tools

Introduction

This guide walks you through connecting Grist to Pydantic AI using the Composio tool router. By the end, you'll have a working Grist agent that can add and update records, create documents and tables, run SQL queries, manage attachments, and set up webhooks through natural language commands.

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

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

Also integrate Grist with

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Grist
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Grist workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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

The Grist MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Grist account. It provides structured and secure access to your spreadsheets and documents, so your agent can perform actions like adding records, creating tables, managing documents, and handling attachments on your behalf.

  • Automated data entry and record management: Instruct your agent to add, update, or delete records in specific Grist tables, streamlining your workflows and reducing manual input.
  • Table and document creation: Let your agent create new tables or entire documents in your workspaces, helping you quickly set up and expand your data structures as your needs grow.
  • Attachment and file management: Ask your agent to remove unwanted attachments from Grist documents, keeping your files organized and storage efficient.
  • Custom webhook integration: Have your agent register or delete webhooks for documents, enabling real-time notifications and integrations with other tools or services you rely on.
  • User and access provisioning via SCIM: Direct your agent to create or delete SCIM users as needed, making it easy to manage who has access to your Grist environment.

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active 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

bash
pip install composio pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Grist
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Grist
  • MCPServerStreamableHTTP connects to the Grist MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Grist
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["grist"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Grist 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
grist_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[grist_mcp],
    instructions=(
        "You are a Grist assistant. Use Grist tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Grist endpoint
  • The agent uses GPT-5 to interpret user commands and perform Grist operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Grist.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Grist API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Grist and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Grist
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["grist"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    grist_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[grist_mcp],
        instructions=(
            "You are a Grist assistant. Use Grist tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Grist.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Grist through Composio's Tool Router. With this setup, your agent can perform real Grist actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Grist for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Add Records

Add one or more records to a Grist table.

Create Document

Creates a new Grist document in a specified workspace.

Create SCIM User

Create a Grist user for SCIM provisioning.

Create Table

Tool to create tables in a document.

Create Document Webhook

Tool to create a new webhook for a specified document.

Remove Unused Attachments

Remove unused attachments from a Grist document to free up storage space.

Delete Column

Tool to delete a column from a Grist document table.

Delete Grist Table Records

Tool to delete records from a specified Grist table.

Delete SCIM User

Delete a Grist SCIM user by numeric user ID.

Delete Webhook

Permanently removes a webhook from a Grist document.

Download All Attachments Archive

Download all attachments from a Grist document as a single archive file (.

Download Attachment

Download a file attachment from a Grist document.

Fetch Document Metadata

Tool to fetch metadata for a specified Grist document.

Fetch Table Metadata

Tool to retrieve metadata for a specified table in a Grist document.

Get Org Access

Retrieves the list of users who have access to a Grist organization along with their access roles (owners, editors, viewers).

Get Users

List Grist users via SCIM v2, with filtering and pagination.

List Attachments

Tool to list all attachments in a Grist document.

List Columns

List columns and their metadata in a specified Grist table.

List Organizations

Tool to list all organizations accessible to the authenticated user.

List Records

Tool to retrieve records from a specified table within a Grist document.

List Tables

Tool to list all tables within a specified document.

List Webhooks

List all webhooks configured for a Grist document.

List Workspaces

Tool to list all workspaces and documents accessible to the authenticated user on the current site.

Run SQL Query

Tool to execute a read-only SQL SELECT query on a Grist document.

Update Column Metadata

Updates metadata (label, type, description, formula, etc.

Update Document Metadata

Tool to update metadata for a specified Grist document.

Update Records

Update existing records in a Grist table by their row IDs.

Update Table Metadata

Update metadata for a table in a Grist document, including its table ID for renaming or its on-demand loading setting.

Update Webhook

Update an existing webhook on a Grist document, changing provided settings such as its URL, event types, enabled status, or target table.

Upload Attachment

Upload one or more file attachments to a Grist document.

FRAMEWORKS

How to build Grist MCP Agent with another framework

Claude Code logo

Claude Code

Use Grist MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Grist MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Grist MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Grist MCP with Claude Agent SDK

Grok Bot logo

Grok Bot

Use Grist MCP with Grok Bot

Codex logo

Codex

Use Grist MCP with Codex

OpenClaw logo

OpenClaw

Use Grist MCP with OpenClaw

Hermes logo

Hermes

Use Grist MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Grist MCP with Atomic Agent

Google ADK logo

Google ADK

Use Grist MCP with Google ADK

LangChain logo

LangChain

Use Grist MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Grist MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Grist MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Grist MCP with LlamaIndex

CrewAI logo

CrewAI

Use Grist MCP with CrewAI

AutoGen logo

AutoGen

Use Grist MCP with AutoGen

FAQ

Frequently asked questions

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