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sudhakar6

Salesforce MCP Server

by sudhakar6

sf_search

Run SOSL keyword searches across multiple Salesforce objects and text fields at once, returning matches grouped by object type. Complements SOQL when exact object/field is unknown.

Instructions

Run a raw SOSL search and return matching records grouped by object type.

Example: FIND {Acme} IN ALL FIELDS RETURNING Account(Name), Contact(Name, Email)

Complements sf_query: SOSL matches keywords across multiple object types and text fields at once, where SOQL needs an exact object and field match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
soslYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the core behavior: executing a raw SOSL query and grouping results by object type. The example also clarifies expected input format. However, it does not address potential side effects, error behavior, permissions, or rate limits; the read-only nature is implied by 'search' but never stated.

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 tight and well-structured: a one-line definition, a concrete example, and a comparative note about sf_query. Every sentence adds value and the example is placed immediately after the core statement, making the tool's usage understandable at a glance.

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?

For a single-parameter tool with no output schema, the description covers the operation, the result shape, and how it differs from a sibling. The example further grounds the expected input. It is not fully exhaustive—missing explicit mention of authentication or error handling—but for this tool's simplicity it is sufficiently complete.

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?

The input schema provides only the parameter name 'sosl' with no description, so the description must compensate. It does so by explaining the tool runs a raw SOSL search and giving a concrete SOSL example with FIND, IN, and RETURNING clauses. This is sufficient for an agent to understand that the parameter expects a full SOSL query string, though a direct parameter description would have been ideal.

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 opens with a specific verb and resource: 'Run a raw SOSL search' and states the output behavior ('return matching records grouped by object type'). It clearly differentiates from sibling sf_query by noting SOSL searches keywords across multiple object types and text fields, whereas SOQL requires exact object and field matches.

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 gives useful decision guidance by positioning itself as a complement to sf_query and explaining the difference between SOSL and SOQL. It implies when to use this tool (multi-object keyword search) but does not explicitly state when not to use it or name fallback conditions, though the contrast with sf_query is fairly clear.

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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