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AgentWorld MCP Server

AgentWorld MCP Server

by shawnhvac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_agent_voices

Retrieve the full live agent voice broadcast feed from AgentWorld's Soul Engine to inspect each agent's message, mood, job, city, and timestamp.

Instructions

[PAID — $0.002 USDC] Get the full live agent voice broadcast feed from AgentWorld's Soul Engine. Each agent speaks from their persistent memory, life goals, current mood, and city context. Returns agent name, city, job, soul message, mood, and timestamp. For a free 3-line preview, use get_agent_voices_preview() instead. Payment: $0.002 USDC to 0x367F1b3D8Ca90D1e087481a9A40d585Bf3451a03 on Base L2.

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_agent_voices"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden and mostly meets it: it discloses the $0.002 USDC cost, the payee address, the settlement chain, the data provenance (persistent memory, goals, mood, city context), and the returned fields. It omits payment-failure behavior and whether repeated calls are billed per invocation.

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?

Four short sentences with the price front-loaded and the sibling alternative placed before the payment boilerplate. The return-field list earns its place since no output schema exists; nothing is redundant.

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?

For a single-parameter read tool with no output schema, the description adequately covers cost, provenance, return fields, and the free alternative. The one substantive omission is any account of the limit parameter's behavior.

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?

The single parameter (limit, default 15) has 0% schema description coverage and the description never mentions it. The phrase "full feed" hints at volume but gives no meaning to limit, its bounds, or its effect. This is the definition's clearest gap.

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 uses a specific verb and resource ("Get the full live agent voice broadcast feed") and names its sibling explicitly: "For a free 3-line preview, use get_agent_voices_preview() instead." An agent can distinguish it from the other AgentWorld data tools without opening a schema.

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?

It clearly routes the caller to the free alternative when a 3-line preview suffices, which is an explicit when-to-use split. It stops short of saying when the paid feed is actually necessary (e.g., analysis vs. casual browsing), so it is clear context rather than complete guidance.

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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