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xrm-mcp

xrm-mcp

by jukkan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_tables

Retrieve Dataverse tables, filtering by custom tables, search term, or publisher prefix, while excluding Microsoft-prefixed solution tables.

Instructions

Lists Dataverse tables. Defaults to custom tables only, excluding Microsoft-prefixed solution tables (msdyn_, msfp_, adx_ etc).

Use prefix='na_' to filter to a specific publisher. Use exclude_ms_prefixes=False to see all custom tables.

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": {
      "org_url": "<org_url>"
    },
    "name": "list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
prefixNoOptional prefix to filter logical names (e.g., "cr123_")
searchNoOptional search term to filter tables
org_urlYesThe Dataverse organization URL (e.g., https://yourorg.crm4.dynamics.com)
custom_onlyNoIf True, only return custom entities (default: True)
exclude_ms_prefixesNoIf True, exclude Microsoft-prefixed solution tables (default: True)

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden. It clearly discloses default filtering behaviors (custom only, excluding Microsoft prefixes) and how to modify them. No destructive or authentication details are needed for a read-only list operation.

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?

Two highly informative sentences with no filler. The default behavior is stated first, followed by two specific usage hints. Every sentence adds value.

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?

Given 5 parameters and an output schema, the description covers defaults and filtering options adequately. It could mention pagination or rate limits, but this is not critical for a read-only list tool.

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 coverage is 100%, providing baseline 3. The description adds meaning beyond the schema with concrete examples like 'na_' for prefix and mentions specific prefixes (msdyn_, msfp_, adx_). This helps agents understand usage beyond parameter types.

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 states the tool 'Lists Dataverse tables' with specific defaults (custom tables only, excluding Microsoft prefixes). It clearly identifies the resource and action, distinguishing from siblings like 'find_table' which searches for a specific table.

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?

Provides guidance on using prefix filtering ('Use prefix='na_' to filter') and the exclude_ms_prefixes parameter ('Use exclude_ms_prefixes=False to see all custom tables'). However, it does not explicitly compare to alternatives like 'find_table' or 'describe_table' for related use cases.

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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