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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 consented website leads for this company and environment

summer_messenger_leads_list
Read-onlyIdempotent

Read consented website leads for this company and environment. Includes volunteered contact details and original submission references.

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>",
      "environment": "<environment>"
    },
    "name": "summer_messenger_leads_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
beforeNo
companyYesSummer company ID
environmentYesEnvironment that owns the resource

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds useful context about what the records contain (volunteered contact details, original submission references) and that only consented leads are returned, but it says nothing about result volume, ordering, or pagination despite there being a cursor-style parameter.

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, front-loaded sentences with no filler; the scope constraint comes first and the payload description second. Slightly padded by restating the title verbatim, but efficient overall.

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?

For a simple read-only list tool with no output schema, the description conveys domain and record shape adequately. However, it omits pagination/cursor behavior and the meaning of the undocumented 'before' parameter, which an agent needs in order to page results correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 67%: company and environment are documented in the schema, but the 'before' parameter has no description anywhere, and its purpose as a time-based cursor is left completely unexplained. The description adds no parameter meaning at all, so it fails to compensate for the coverage gap.

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 states a specific verb and resource (read consented website leads) scoped to a company and environment, and the second sentence names the payload contents. It is clearly distinguishable from sibling messenger tools such as conversations_list or email_read, though it never names an alternative explicitly.

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?

There is no statement of when to use this tool versus alternatives, no prerequisites, and no exclusions. An agent must infer usage entirely from the name and the readOnly annotation.

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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