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Rows MCP Server for Pydantic AIGive Pydantic AI instant access to 11 tools to Append Values To Table, Create Spreadsheet, Delete Spreadsheet, and more

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Rows through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Rows app connector for Pydantic AI is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Rows "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Rows?"
    )
    print(result.data)

asyncio.run(main())
Rows
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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Rows MCP Server

Connect your Rows.com account to any AI agent and take full control of your spreadsheet-based data orchestration and collaborative workflows through natural conversation. Rows provides a modern spreadsheet platform with built-in integrations, and this integration allows you to retrieve row metadata, update cell values, and perform complex data queries directly from your chat interface.

Pydantic AI validates every Rows tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

  • Spreadsheet & Table Orchestration — List all managed spreadsheets and retrieve detailed metadata, including table structures programmatically.
  • Data Value Intelligence — Access and monitor range values to retrieve real-time spreadsheet data directly from the AI interface.
  • Cell Lifecycle Management — Update and append values to specific ranges to ensure your records are always synchronized via natural language.
  • Folder & Organization Control — List and search through your folders to maintain a clear overview of your digital workspace.
  • Operational Monitoring — Track system activity and manage spreadsheet metadata using simple AI commands to streamline your business workflows.

The Rows MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 11 Rows tools available for Pydantic AI

When Pydantic AI connects to Rows through Vinkius, your AI agent gets direct access to every tool listed below — spanning spreadsheets, data-queries, collaborative-data, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

append_values_to_table

Add new rows to a table

create_spreadsheet

Create a new spreadsheet

delete_spreadsheet

Delete a spreadsheet

get_folder

Get details for a specific folder

get_range_cells

Get detailed cell objects

get_range_values

g., A1:B5). Get values from a specific range

get_spreadsheet_details

Get metadata for a spreadsheet

get_workspace_info

Get Rows workspace details

list_folders

List workspace folders

list_spreadsheets

List your Rows spreadsheets

update_range_values

Overwrite values in a range

Connect Rows to Pydantic AI via MCP

Follow these steps to wire Rows into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 11 tools from Rows with type-safe schemas

Why Use Pydantic AI with the Rows MCP Server

Pydantic AI provides unique advantages when paired with Rows through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Rows integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Rows connection logic from agent behavior for testable, maintainable code

Rows + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Rows MCP Server delivers measurable value.

01

Type-safe data pipelines: query Rows with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Rows tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Rows and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Rows responses and write comprehensive agent tests

Example Prompts for Rows in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Rows immediately.

01

"List all spreadsheets in my Rows workspace."

02

"Show me all spreadsheets in my workspace and pull the latest data from the Sales Dashboard."

03

"Create a new spreadsheet called Q3 Planning and populate it with department budget data."

Troubleshooting Rows MCP Server with Pydantic AI

Common issues when connecting Rows to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Rows + Pydantic AI FAQ

Common questions about integrating Rows MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Rows MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.