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Microsoft Graph MCP Server

Microsoft Graph MCP Server

by oliverhruby
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

append_table_row

Add a new row to an Excel table by providing the file, table, and cell values as a JSON array.

Instructions

Append a row to a table. values_json: JSON 1D array of cell values.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_id": "<file_id>",
      "table_id": "<table_id>",
      "values_json": "<values_json>"
    },
    "name": "append_table_row"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_idYes
table_idYes
values_jsonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It only states that a row is appended and gives the values_json format. It does not disclose whether the operation is irreversible, what response is returned, or how the row is ordered.

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

Conciseness5/5

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

The description is a single focused sentence followed by a brief, essential parameter detail. There is no redundancy or filler; every word adds value.

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

Completeness3/5

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

For a simple three-parameter mutation, the description covers the core action and the most complex parameter format. However, it omits response behavior, column-count constraints, and selection guidance relative to sibling tools, leaving it minimally viable but incomplete.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It explains values_json as a 'JSON 1D array of cell values,' adding useful meaning. However, file_id and table_id are only named in the schema with no additional context.

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

Purpose4/5

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

The description states a clear verb and resource: 'Append a row to a table.' This is specific enough to distinguish the operation from sibling tools like update_table_row or write_range, though it does not explicitly name alternatives.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus update_table_row, write_range, or create_table. It also lacks prerequisites such as needing the table to already exist or how to obtain file_id/table_id.

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

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