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AgentWorld MCP Server

AgentWorld MCP Server

by shawnhvac
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

data_economy

Fetches live AgentWorld economy metrics—agent count, USDC circulation, transaction totals, treasury, and Gini coefficient—to support current city-economy analysis.

Instructions

[DATA] Live economy snapshot from the dataset: agent count, total USDC in circulation, total transactions (2.5M+), treasury, Gini coefficient. ($0.001 USDC.)

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": "data_economy"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose two genuinely useful behavioral facts the schema cannot: the call is a live snapshot (not cached history) and it costs $0.001 USDC. It never explicitly states the call is read-only with no side effects, nor anything about freshness or response shape.

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?

A single dense sentence plus price, front-loaded with the field list and no filler. The parenthetical '$0.001 USDC' is well placed at the end. Slightly list-heavy, but every item named is return-value information an agent needs.

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?

With no output schema, the description must say what comes back, and it does so field by field, which is the right call for a zero-parameter snapshot tool. The one real gap is the unresolved overlap with the sibling get_economy.

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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. Nothing in the description misleads about inputs.

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 resource (live economy snapshot) and enumerates the exact fields returned: agent count, USDC in circulation, total transactions, treasury, Gini coefficient. That is far more concrete than the name alone. It does not, however, distinguish itself from the sibling get_economy, which by name appears to cover the same ground.

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 when-to-use guidance at all: no mention of when this beats get_economy, get_arena_tokenomics, or get_city_stats, and no stated preconditions. The only routing signal is the '[DATA]' prefix, which hints at a dataset-backed variant but is never explained.

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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