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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 scheduled agent jobs, names, instructions, schedules, next runs and latest results

summer_scheduled_jobs_list
Read-onlyIdempotent

Read company scheduled agent jobs, names, instructions, schedules, next runs and latest results. These independent jobs use company knowledge and connected tools; source collection precedes ordinary case routing.

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_scheduled_jobs_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
companyYes
environmentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description adds the useful detail that these are independent jobs drawing on company knowledge and connected tools, but offers nothing on pagination, result ordering, or freshness of 'latest results' — modest added value over the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence is a dense but front-loaded enumeration of what is returned. The second sentence ('source collection precedes ordinary case routing') is jargon-heavy and its relevance to calling a list endpoint is unclear, so it does not clearly earn its place.

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 description compensates partly for the absent output schema by naming the returned fields, and annotations cover safety. But with two required, undocumented parameters and no output schema, an agent still lacks enough to call this confidently versus the sibling runs/history tools.

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 description coverage is 0% and the description never mentions either required parameter. An agent gets no explanation of why a company UUID and a production/staging environment are mandatory, or what changing environment implies for the returned data — precisely the kind of gap the description should fill at zero coverage.

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 scheduled agent jobs') and enumerates the fields returned (names, instructions, schedules, next runs, latest results). It does not, however, distinguish itself from the closely named siblings summer_scheduled_jobs_runs and summer_scheduled_jobs_history, leaving the agent to infer the difference.

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 explicit when-to-use guidance and no mention of the sibling tools (_runs, _history, _run, _save) that an agent must choose between. The second sentence offers conceptual context about how these jobs operate but says nothing about when this list tool is the right call.

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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