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sunny980123

Salesforce MCP Server

by sunny980123

List Salesforce Objects

salesforce_list_objects
Read-onlyIdempotent

List all standard and custom Salesforce objects in your org, with optional filtering by name or label, and control over queryable-only status, limit, and output format.

Instructions

List all available Salesforce objects (standard and custom) in the org.

Use this to discover what objects exist before querying or manipulating data.

Args:

  • filter (string): Optional text to filter object names/labels (case-insensitive)

  • queryable_only (boolean): If true, only return objects that support SOQL queries (default: true)

  • limit (number): Maximum number of objects to return (default: 50, max: 500)

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: List of objects with their names, labels, and CRUD capabilities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of objects to return (default: 50)
filterNoOptional text filter applied to object name or label (case-insensitive)
queryable_onlyNoIf true, only return objects that support SOQL queries
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds behavioral context by describing the return value ('List of objects with their names, labels, and CRUD capabilities'), which is not covered by annotations.

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 concise with clear sections (purpose, usage, args, returns). Every sentence adds value, and the structure is well-organized for quick scanning.

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?

Given the rich annotations, full schema coverage, and no output schema, the description adequately explains the tool's behavior and return value. It is complete for an agent to understand how to use it.

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 coverage is 100% with detailed parameter descriptions. The description in the Args section largely mirrors the schema (e.g., 'filter (string): Optional text to filter object names/labels (case-insensitive)'), adding minimal new meaning beyond what the schema already provides.

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 explicitly states 'List all available Salesforce objects (standard and custom) in the org,' using a specific verb and resource. It distinguishes this tool from siblings like salesforce_query (querying data) and salesforce_describe_object (describing a specific object), making its purpose clear.

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 says 'Use this to discover what objects exist before querying or manipulating data,' providing clear guidance on when to use it. It does not explicitly exclude scenarios, but the context of sibling tools implies alternatives for data operations.

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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