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aaronsb

Salesforce MCP Server

by aaronsb
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TypeScript
Remote

analyze

Run analytics on any Salesforce object by grouping categorical fields, aggregating numeric values, and computing custom expressions to derive insights.

Instructions

Run analytics on any Salesforce object — group by categorical fields, aggregate numeric fields, and compute custom expressions. Uses field-type metadata for validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoSOQL WHERE clause (e.g., "StageName = 'Closed Won' AND Amount > 100000")
objectYesSalesforce object API name (e.g., Opportunity, Account, Lead)
computeNoComputed expressions (max 5). Format: name = expr. E.g., ["win_rate = won / total * 100"]
groupByNoField to group by (must be picklist, boolean, or similar categorical field)
maxGroupsNoMax groups to return (default: 20)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.2
  2. Removedv0.7.2
  3. First observedv0.5.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It discloses metadata validation but omits side effects, permissions, rate limits, or return format. The absence of these details leaves significant uncertainty about runtime behavior.

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 that front-loads the primary purpose. It is concise, readable, and free of unnecessary jargon or redundancy.

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?

The tool has a moderate parameter set and no output schema. While the core functionality is described, the absence of output details and usage guidance leaves room for ambiguity in real-world invocation.

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?

All five parameters have descriptions with concrete examples (e.g., SOQL WHERE clause, expression format, default max groups). The descriptions add meaningful detail beyond the parameter names, achieving high coverage and clarity.

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 clearly states the tool runs analytics on Salesforce objects with grouping, aggregation, and custom expressions. It distinguishes itself from raw SOQL execution and object listing, though it does not explicitly name sibling tools.

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?

The description provides no explicit guidance on when to use this tool versus alternatives like execute_soql or describe_object. It only mentions metadata-based validation, which hints at behavior but not usage context.

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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