Rows MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Append Values To Table, Create Spreadsheet, Delete Spreadsheet, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Rows as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Rows app connector for LlamaIndex 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
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Rows. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Rows?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Rows tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex
When LlamaIndex 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.
Add new rows to a table
Create a new spreadsheet
Delete a spreadsheet
Get details for a specific folder
Get detailed cell objects
g., A1:B5). Get values from a specific range
Get metadata for a spreadsheet
Get Rows workspace details
List workspace folders
List your Rows spreadsheets
Overwrite values in a range
Connect Rows to LlamaIndex via MCP
Follow these steps to wire Rows into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Rows MCP Server
LlamaIndex provides unique advantages when paired with Rows through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Rows tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Rows tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Rows, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Rows tools were called, what data was returned, and how it influenced the final answer
Rows + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Rows MCP Server delivers measurable value.
Hybrid search: combine Rows real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Rows to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Rows for fresh data
Analytical workflows: chain Rows queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Rows in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Rows immediately.
"List all spreadsheets in my Rows workspace."
"Show me all spreadsheets in my workspace and pull the latest data from the Sales Dashboard."
"Create a new spreadsheet called Q3 Planning and populate it with department budget data."
Troubleshooting Rows MCP Server with LlamaIndex
Common issues when connecting Rows to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRows + LlamaIndex FAQ
Common questions about integrating Rows MCP Server with LlamaIndex.