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AI Takeover Tracker MCP Server

AI Takeover Tracker MCP Server

by sooter8
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_latest_score

Retrieve the current AI Takeover Index score to monitor AI's progress in automating white-collar work. This daily composite score (0-100%) helps track automation trends.

Instructions

Get the current AI Takeover Index — a daily composite score (0-100%) tracking AI's progress toward automating white-collar work. Updated daily at aitakeovertracker.com.

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": "get_latest_score"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the score is 'daily composite' and 'updated daily,' which adds useful behavioral context about data freshness. However, it lacks details on potential errors, rate limits, or authentication needs, leaving gaps for a tool with no annotation coverage.

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 a single, well-structured sentence that efficiently conveys the tool's purpose, what the score represents, and update frequency. Every part adds value without redundancy, making it appropriately sized and front-loaded.

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 tool's simplicity (0 parameters, no output schema, no annotations), the description is largely complete, covering purpose and behavior. However, without an output schema, it could benefit from mentioning the return format (e.g., numeric score or structured data), slightly reducing completeness.

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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, earning a baseline score of 4 for not adding unnecessary information beyond the schema.

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 specific action ('Get') and resource ('current AI Takeover Index'), including what it is ('a daily composite score (0-100%) tracking AI's progress toward automating white-collar work'). It distinguishes this tool from siblings by focusing on a specific index score rather than blog posts, news, occupations, etc.

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 provides clear context for when to use this tool ('Get the current AI Takeover Index'), including its purpose and update frequency ('Updated daily'). However, it does not explicitly state when not to use it or name alternatives among siblings, such as when other tools might be more appropriate for related data.

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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