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Smartsheet MCP. Query your entire company grid from chat.

Claude Claude
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Just plug in your AI agents and start using Vinkius.

Smartsheet MCP Server lets your AI agent read, map, and query all your company's structured data grids without leaving your code editor.

Use it to list workspaces, find specific sheets, pull raw rows and columns from any grid, or check user permissions—all via natural conversation.

What your AI agents can do

Get current user

Pulls details about the Smartsheet user account currently connected to the agent.

Get sheet details

Retrieves all columns and rows for a single, specified spreadsheet grid.

List folders

Lists every folder within the user's connected Smartsheet workspace.

+ 3 more capabilities included
Discover your entire grid structure

List all top-level workspaces, folders, and sheets to map out exactly where project data lives.

Extract raw sheet data by ID

Target a specific spreadsheet and pull the full metadata—all columns and rows—for deep analysis.

View system reports

List all pre-built, saved tabular aggregations that summarize data across multiple sheets.

Check user permissions

Determine the agent's current access scope by retrieving information about the connected Smartsheet user.

Supported MCP Clients

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients
Free for Subscribers

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AI Agent

Smartsheet MCP Server: 6 Tools for Data Grids

These tools give your agent the ability to navigate Smartsheet's entire structure. You can list workspaces, find sheets, pull data rows, and check user permissions.

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get current user

Pulls details about the Smartsheet user account currently connected to the agent.

get019d7609

get sheet details

Retrieves all columns and rows for a single, specified spreadsheet grid.

list019d7609

list folders

Lists every folder within the user's connected Smartsheet workspace.

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list reports

Retrieves a list of all saved, aggregated reports across configured company sheets.

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list sheets

Provides an inventory of every available sheet grid in the connected Smartsheet account.

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list workspaces

Lists all top-level workspaces that contain multiple project folders and sheets.

Choose How to Get Started

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Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

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Start with Smartsheet, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.

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  • Works with Claude, ChatGPT, Cursor, and more
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What you can do with this MCP connector

Stop jumping between tabs. This server lets your AI client talk directly to all your company's Smartsheet grids—you can query, map, and pull raw data without ever leaving your code editor. It handles everything from finding a specific project sheet to checking who you are in the system.

Discovering Your Grid Structure

You need to know where the data lives before you touch it. You start by listing all top-level workspaces using list_workspaces. That shows you every major container of projects and sheets your team uses across the organization. From there, you can drill down into specific sections; list_folders pulls up an inventory of every single folder within a chosen workspace, giving you that full project hierarchy map.

To see what grids are actually available for work, run list_sheets. This tool gives you a clean list of every active spreadsheet grid attached to your account. You can combine these tools—you'll use them in sequence to trace the exact path from a top workspace down through folders and finally to the sheet itself.

Pulling Raw Data & Reports

Once you know which sheets exist, you pull the data. If you target a specific spreadsheet by its ID, get_sheet_details pulls everything: it grabs all columns and every single row of metadata for deep analysis. You don't just get a summary; you get the raw dump. For high-level summaries, you can use list_reports.

This tool retrieves a list of pre-built, saved reports—these are complex aggregations that summarize data across multiple company sheets, letting your agent know exactly what views already exist without needing to build them from scratch.

Checking System Context and Permissions

Before you write a single line of code, you check the context. You run get_current_user; this pulls all the details about the Smartsheet user account your agent is currently connected to. This lets it verify connectivity and understand its current access scope right out of the gate. By checking the user details first, you'll know exactly what kind of permissions you have when you try querying data or listing grids.

It’s a comprehensive system for understanding where all your structured project data is located—you map the top workspaces with list_workspaces, drill into the containers using list_folders, get the list of available sheets via list_sheets, and then finally use get_sheet_details to extract every single row and column you need. You'll also pull up all system reports with list_reports and keep a tight grip on what your agent can actually see using get_current_user.

This lets your AI client treat your entire grid setup like one giant, queryable database.

How Smartsheet MCP Works

  1. 1 Subscribe to this server and enter your personal Smartsheet Access Token.
  2. 2 Connect a compatible client (like Cursor or Claude) to the MCP Server.
  3. 3 Ask your agent a question—for example, 'List all sheets in the Marketing department.' The agent then runs the necessary tool calls (list_sheets) and returns the data.

The bottom line is: Your AI client talks directly to Smartsheet's API through these tools, letting you query complex grids without writing any Python or sheet-specific code.

Who Is Smartsheet MCP For?

Project Managers who are sick of manually tracking down which spreadsheet holds the most current task list. Data Engineers who need to programmatically map out an entire company's data structure before writing a single ETL script. Team Leaders who need autonomous reports without spending hours compiling CSV exports.

Project Manager

Audits cross-functional sheets by running list_reports to get quick overviews of tasks, rather than exporting dozens of separate files.

Data Engineer

Queries the actual sheet layout and metadata using get_sheet_details directly from the code editor to build robust data pipelines.

Team Leader

Asks the bot to read specific project spreadsheets via natural language, generating preliminary summary drafts without manual intervention.

What Changes When You Connect

  • Stop hunting for sheet IDs. Use list_workspaces and list_sheets to map out every data source automatically, saving you hours of manual discovery time.
  • Need a quick status update? Running list_reports pulls aggregated views across multiple grids instantly, bypassing the need to export 10 different CSVs for a single summary.
  • Data Engineers: Skip setting up boilerplate API calls. Call get_sheet_details and pull raw row/column metadata directly into your script's context.
  • Context is king. Use get_current_user early in your workflow to verify the agent's authorized scope, preventing run-time permission errors.
  • Navigate like a pro: Call list_folders after identifying a workspace (list_workspaces) to drill down into exactly where the relevant project files live.

Real-World Use Cases

01

Auditing cross-functional tasks

A Project Manager needs to see task status across three different department sheets. Instead of manually opening and comparing them, they ask their agent: 'List all reports related to Q3.' The agent uses list_reports and then pulls the aggregated data via get_sheet_details, giving a single, unified view.

02

Building an ETL script

A Data Engineer needs to know every sheet available before starting a migration. They prompt: 'List all sheets and their metadata.' The agent uses list_sheets and then can inspect the structure of each using get_sheet_details, allowing the engineer to build a comprehensive, sturdy script.

03

Weekly status summary generation

A Team Leader needs to draft weekly progress reports. They ask their agent to 'Read all sheets under the Core Engineering workspace.' The agent runs list_workspaces first, then uses a combination of listing and detail retrieval to gather text blocks from multiple grids autonomously.

04

Onboarding new team members

A manager needs to show a new hire where all documents are. They ask the agent: 'Show me the entire document structure.' The agent runs list_workspaces and then list_folders, providing a clear, navigable map of the company's data architecture.

The Tradeoffs

Trying to query by memory

The user thinks they know the exact ID for 'Q3 Marketing Budget,' but it's buried in a folder and they don't want to click through 15 subfolders.

Don't guess. First, use list_workspaces to see the top-level containers. Then, drill down with list_folders until you find the correct path. Finally, run list_sheets in that folder to get the precise ID.

Overloading one function call

Trying to ask: 'Give me everything about the marketing stuff.' This prompt is too vague and doesn't tell the agent which data source to focus on.

Be specific with your tools. First, use list_reports to get a list of reports; then, specify which report you want details for.

Assuming sheet availability

The user expects the agent to know about a new prototype sheet that hasn't been indexed or linked yet.

Always start by running list_sheets. This confirms what Smartsheet has visibility on, so you don't waste time asking for data from non-existent grids.

When It Fits, When It Doesn't

Use this server if your core problem involves interacting with highly structured, grid-based data (like spreadsheets). If you need to read rows and columns, check folder hierarchies, or pull summary reports generated by Smartsheet itself, this is the right tool. Don't use it if your data lives in a simple unstructured text file, an email thread, or a purely relational database that doesn't expose its structure through grids. For those cases, you need a different type of connector (like a SQL-type agent). If your only goal is to list files and folders outside of the grid context, this server still helps by mapping the path (list_folders), but it can't replace a dedicated file system API.

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Smartsheet. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.

Available Capabilities

get_current_user get_sheet_details list_folders list_reports list_sheets list_workspaces

Manually tracking down data across dozens of grids sucks.

Today, getting an overview of project status means logging into Smartsheet. You open the 'Budget Tracker,' then jump to the 'HR Roster' sheet, and finally pull up the 'Q3 Goals Dashboard.' Then you copy three different sets of numbers into a single document—a time-sink that guarantees version control problems.

With this MCP server, your AI agent handles the navigation. You simply tell it what project overview you need. It uses `list_workspaces` to find the right container, runs `get_sheet_details` on every relevant sheet in the background, and presents a consolidated report—all without you ever leaving your code editor.

Smartsheet MCP Server: Get structured data straight into your workflow.

The biggest time-waster is the context switching. You have to click, navigate tabs, find IDs, and then copy/paste metadata just to write a simple script. This manual process breaks focus and creates errors every single time.

Now, your agent uses `list_sheets` and `get_sheet_details`. It pulls the data structure directly into the language model's context window. You get clean, usable, structured output ready for scripting—no copies, no pastes, just pure data.

Common Questions About Smartsheet MCP

How do I list all available sheets in Smartsheet using the `list_sheets` tool? +

You ask your agent to run list_sheets. It will return an inventory of every sheet grid accessible from your connected account. This is key for discovering data sources you might not know exist.

Can I get the raw data rows using `get_sheet_details`? +

Yes, that's exactly what it does. You give it a sheet ID, and it returns all the column headers and every single row of data contained in that grid.

What is the difference between `list_sheets` and `list_reports`? +

Sheets are individual grids where people input raw data. Reports, found via list_reports, are pre-built dashboards or aggregated views that summarize data from one or more underlying sheets.

How does the agent find my project location? Should I use `list_workspaces`? +

Start with list_workspaces. This tool maps out your top-level containers. You'll see a list of workspaces, which lets you narrow down where the specific projects are stored.

What information does `get_current_user` provide regarding my access scope? +

It returns metadata about your account, including authorized scopes. This lets you confirm what permissions the agent has before querying sensitive data like full sheets or reports.

How do I use `list_folders` to map out a specific project's file hierarchy? +

list_folders shows all folders within a given workspace ID. You can chain these calls to build a complete path, helping your agent locate the exact document you need.

Does `get_sheet_details` retrieve column names and data types, or just rows? +

It provides both the raw row data and structural metadata. This means you can see the sheet's column names (e.g., 'Status', 'Date') along with their defined format.

When I run `list_workspaces`, how does it determine which workspaces are available to me? +

The tool accesses your Smartsheet account using the provided access token. It simply lists all top-level workspaces that your user profile has been granted visibility over.

Can the AI understand the raw tabular data of my spreadsheet? +

Yes. When you call the get_sheet_details tool, the server returns the spreadsheet's metadata, including all column names, types (e.g., date, dropdown), and rows. The AI maps the internal IDs together to form a highly accurate contextual grid of your project.

Does my agent need to use a sheet ID? +

No manual hunting needed! While the underlying tool does require a sheet ID, you can just tell your bot, 'Find our Onboarding Spreadsheet and read the rows'. The AI will first scan via list_sheets, match the textual name to the ID, and then naturally pull the targeted entity.

How do I list folders within a workspace? +

Your AI agent will act autonomously. Ask it to 'check our Engineering workspace' and it will first fetch its workspace ID and intelligently map the nested sub-folders and sheets stored inside. You can instruct it to keep going deeper as needed.

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Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
+ other MCP clients

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