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This connector has been deprecated

This was a duplicate manual listing. Use Summer’s official listing, imported from the official MCP Registry. Summer’s MCP server remains active at https://api.gosummer.ai/mcp. Setup and documentation: https://gosummer.ai/docs/mcp-clients.

Read company-wide settings, including the email subject customers see on new support emails

summer_company_settings_read
Read-onlyIdempotent

Read company-wide settings, including the email subject customers see on new support emails. Changes affect every environment.

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": {
      "company": "<company>"
    },
    "name": "summer_company_settings_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
companyYesSummer company ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered. The description adds that settings are company-wide and apply across every environment, which is useful scope context, but the sentence 'Changes affect every environment' is framed around mutation and is somewhat misplaced on a read-only tool.

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?

Two short sentences with the resource stated first and the concrete field example second. The trailing 'Changes affect every environment' sentence is arguably wasted or confusing on a read tool, but overall there is no bloat.

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?

With one fully documented parameter, full annotation coverage and no output schema, the description supplies enough for correct invocation and gives a hint of returned content ('email subject customers see'). A fuller enumeration of the settings returned would close the remaining gap.

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% for the single 'company' parameter (Summer company ID), so the schema carries the semantics. The description reinforces the company-wide scope but adds no format, sourcing, or lookup detail beyond what the schema already provides; baseline 3 applies.

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?

States a specific verb (Read) and resource (company-wide settings) and names a concrete example field, the customer-facing email subject. The read/update split is carried by the tool name rather than the description, so it is clear but not explicitly differentiated from summer_company_settings_update.

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 gives no when-to-use guidance, no prerequisites, and no routing to adjacent read tools such as summer_company_setup_status, summer_company_capabilities, or summer_company_team_read. The only cue is the verb 'Read', leaving the agent to infer the context entirely.

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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