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tableau-graphql-mcp

tableau-graphql-mcp

by tdries
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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introspect_schema

Read-only

Inspect the live Tableau Metadata API GraphQL schema to discover query entry points, types, fields, and arguments, so you can write correct queries against the server.

Instructions

Introspect the live Metadata API GraphQL schema (introspection is enabled).

With no argument: returns every Query entry point (with its args) and the full list of
type names. With `type_name` (e.g. "Column", "Workbook", "DatabaseTable", "CalculatedField"):
returns that type's fields, their result types, and args, so you can write a correct query
against exactly what this server exposes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "introspect_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
type_nameNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint=true, destructiveHint=false, openWorldHint=true). The description adds real context beyond them: that introspection is enabled on this server, and what each invocation mode returns. It does not discuss error behavior for an invalid type name.

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?

Front-loaded with the action and its scope, then splits cleanly into the no-arg and type_name cases. Every sentence carries information; nothing is padding.

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

Completeness4/5

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

With an output schema present and annotations covering safety, the description only needs to explain modes and the parameter, which it does. The one notable omission is any hint about failure behavior for a nonexistent type name.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the parameter — and it does, explaining that `type_name` is optional, what happens when omitted, and giving concrete example values ("Column", "Workbook", "DatabaseTable", "CalculatedField"). Case sensitivity and invalid-value handling are left unstated.

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?

Specific verb+resource: "Introspect the live Metadata API GraphQL schema" names exactly what is being inspected and what the two modes yield. It does not name a sibling (e.g. graphql_query) explicitly, so the differentiation is only implicit, which keeps it out of the top band.

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 clearly states the two usage contexts — no argument for entry points/type names, `type_name` for a specific type's fields — and frames the purpose as "so you can write a correct query." It gives no explicit when-not or named alternative, so it stops short of 5.

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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