Skip to main content
Glama
redesignhealth

Google Workspace MCP Server

create_table_with_data

Create a table in a Google Doc and populate it with structured data in a single reliable operation. Use inspect_doc_structure first to get the correct insertion index.

Instructions

Creates a table and populates it with data in one reliable operation.

CRITICAL: YOU MUST CALL inspect_doc_structure FIRST TO GET THE INDEX!

MANDATORY WORKFLOW - DO THESE STEPS IN ORDER:

Step 1: ALWAYS call inspect_doc_structure first Step 2: Use the 'total_length' value from inspect_doc_structure as your index Step 3: Format data as 2D list: [["col1", "col2"], ["row1col1", "row1col2"]] Step 4: Call this function with the correct index and data

EXAMPLE DATA FORMAT: table_data = [ ["Header1", "Header2", "Header3"], # Row 0 - headers ["Data1", "Data2", "Data3"], # Row 1 - first data row ["Data4", "Data5", "Data6"] # Row 2 - second data row ]

CRITICAL INDEX REQUIREMENTS:

  • NEVER use index values like 1, 2, 10 without calling inspect_doc_structure first

  • ALWAYS get index from inspect_doc_structure 'total_length' field

  • Index must be a valid insertion point in the document

DATA FORMAT REQUIREMENTS:

  • Must be 2D list of strings only

  • Each inner list = one table row

  • All rows MUST have same number of columns

  • Use empty strings "" for empty cells, never None

  • Use debug_table_structure after creation to verify results

Args: user_google_email: User's Google email address document_id: ID of the document to update table_data: 2D list of strings - EXACT format: [["col1", "col2"], ["row1col1", "row1col2"]] index: Document position (MANDATORY: get from inspect_doc_structure 'total_length') bold_headers: Whether to make first row bold (default: true)

Returns: str: Confirmation with table details and link

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes
table_dataYes
document_idYes
bold_headersNo
user_google_emailYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and succeeds. It discloses the critical dependency on inspect_doc_structure, the exact source and validity requirements for the index, data format constraints, and post-creation verification via debug_table_structure. It also states the return value and default for bold_headers.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with critical information. However, the same index-related warning is repeated multiple times in slightly different forms, adding unnecessary length. Still, the level of detail is justified by the tool's cross-tool dependency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all five parameters, the required sibling-tool call, validation rules, a data format example, the return type, and a verification step. With the output schema also present, an agent has everything needed to use this tool correctly. No major gaps are evident.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates fully. Every parameter is explained in the Args section, including the exact 2D-list format for table_data, the mandatory source for index, and the default for bold_headers. A worked example further clarifies usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Creates a table and populates it with data in one reliable operation.' This is a specific verb+resource combination and distinguishes it from generic document-insertion tools like insert_doc_elements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit mandatory workflow: must call inspect_doc_structure first, use total_length as the index, and verify with debug_table_structure. It does not explicitly name alternative tools or state when not to use this tool, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/redesignhealth/google-mcp-unofficial'

If you have feedback or need assistance with the MCP directory API, please join our Discord server