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OpenTweet MCP Server

OpenTweet MCP Server

Official
by opentweetio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

opentweet_get_evergreen_settings

Read-only

Check your evergreen queue settings and pool statistics to see if the queue is enabled, the posting frequency, cooldown, and pool size limits.

Instructions

Get your evergreen queue settings and pool statistics. Shows whether the queue is enabled, posting frequency, cooldown, and pool size limits.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "opentweet_get_evergreen_settings"
  }
}

Input Schema

NameRequiredDescriptionDefault
x_account_idNoFilter by X account ID (for multi-account users)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the read-only behavior is clear. The description adds valuable context by listing the specific data returned (queue enabled, frequency, cooldown, pool size limits), enhancing transparency beyond the annotation.

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 extremely concise, consisting of just two sentences. The first states the tool's overall purpose, and the second lists the specific outputs. Every sentence serves a clear function with no wasted words.

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?

Given the simple input (one optional parameter) and lack of output schema, the description adequately explains what the tool does and what it returns. It covers the key points, though it might benefit from mentioning the response format or that there is no output schema.

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?

The only parameter (x_account_id) has a description in the schema (100% coverage), and the tool description does not add any additional semantic information. According to guidelines, baseline is 3 when schema coverage is high.

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 clearly states the verb 'Get' and the resource 'evergreen queue settings and pool statistics'. It specifies the exact information returned (enabled, frequency, cooldown, pool size limits), distinguishing it from sibling tools like opentweet_list_evergreen_posts and opentweet_update_evergreen_settings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for viewing settings and statistics, but it does not explicitly state when to use it versus alternatives, nor does it mention prerequisites or context. It provides minimal guidance on usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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