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mafzaal

Dynamics 365 Finance & Operations MCP Server

by mafzaal

d365fo_get_table_info

Retrieve detailed metadata for Dynamics 365 Finance & Operations database tables, including column definitions, constraints, indexes, statistics, and relationships to support query development and data exploration.

Instructions

Get detailed information about a specific database table including:

  • Column definitions with types, nullability, and defaults

  • Primary and foreign key constraints

  • Indexes and their characteristics

  • Table statistics (row count, size, last updated)

  • Sample data (first few rows)

  • Relationships to other tables

This tool is useful for exploring specific tables before writing queries.

Args: table_name: Name of the table to get information about (e.g., 'data_entities', 'public_entities', 'entity_properties'). include_sample_data: Include sample data from the table (first 5 rows). include_relationships: Include information about relationships to other tables. profile: Configuration profile to use (optional - uses default profile if not specified)

Returns: Dictionary with table information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYes
include_sample_dataNo
include_relationshipsNo
profileNodefault
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by specifying what information is returned (column definitions, constraints, etc.) and the optional nature of sample data and relationships. However, it doesn't mention performance characteristics (e.g., whether this is a heavy operation), authentication requirements, rate limits, or error conditions. For a tool with no annotation coverage, this leaves some behavioral aspects unclear.

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 with a clear purpose statement, bulleted list of what's included, usage context, and separate sections for arguments and returns. Every sentence earns its place, though the bulleted list could be slightly more concise. It's appropriately sized for a tool with multiple parameters and rich functionality.

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?

Given the tool's complexity (4 parameters, detailed table metadata) and the absence of both annotations and output schema, the description does a reasonable job. It explains what information is returned and documents all parameters. However, without an output schema, it doesn't specify the exact structure of the returned dictionary, which leaves some ambiguity about the response format. For a metadata exploration tool, more detail about the return structure would be helpful.

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?

With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. It successfully explains all four parameters: 'table_name' is clarified with examples ('data_entities', 'public_entities'), 'include_sample_data' specifies what it includes ('first 5 rows'), 'include_relationships' explains its purpose, and 'profile' describes its optional nature and default behavior. The description adds substantial value beyond the bare schema.

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 specific action ('Get detailed information about a specific database table') and enumerates exactly what information is retrieved (column definitions, constraints, indexes, statistics, sample data, relationships). It distinguishes itself from siblings like 'd365fo_get_database_schema' (which likely provides broader schema overview) and 'd365fo_get_entity_schema' (which might focus on entity-level metadata) by targeting detailed table-level metadata.

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 clear context for when to use this tool ('useful for exploring specific tables before writing queries'), which helps the agent understand its exploratory purpose. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools (e.g., when to use 'd365fo_execute_sql_query' or 'd365fo_get_database_schema' instead).

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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