Carbon Copy MCP Server

Official

by usehoplite

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Discover Traders

discover_traders

Read-only

Search and rank traders by ROI, volume, win rate, and other metrics to identify the best traders to follow for copy trading.

Instructions

Search and rank traders available to follow.

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": "discover_traders"
  }
}

Input Schema

Name	Required	Description
`q`	No	Search term for trader username/wallet.
`limit`	No	Maximum number of traders to return.
`minRoi`	No	Minimum ROI percentage.
`sortBy`	No	Sort mode for discovered traders.
`minVolume`	No	Minimum all-time volume in USD.
`minWinRate`	No	Minimum win rate percentage.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.4.1Aug 10, 2026

TDQS

B3.1/5.0

Behavior3/5

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

The annotation readOnlyHint=true already covers the safety profile, so the bar is lower. The description adds minimal behavioral context, only stating that it searches and ranks traders. It does not disclose result formatting, pagination, or default sorting behavior, but it does not contradict the annotations either.

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?

The description is a single sentence with no wasted words, making it appropriately concise. However, given the tool has six parameters, this brevity is borderline under-specified; still, it is well-structured and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is very sparse for a tool with six parameters and no output schema. It does not explain how discover_traders relates to siblings like list_traders, nor does it describe ranking logic or result types. The annotation provides safety, but the description lacks sufficient context for an agent to make a fully informed choice.

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 input schema has 100% description coverage for all six parameters, so the schema carries the parameter semantics. The description itself does not mention parameters, but given the high schema coverage, the baseline of 3 is appropriate.

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?

The description uses a specific verb phrase 'search and rank' with the resource 'traders', clearly indicating a discovery operation. It also adds the context 'available to follow', which helps differentiate from simple listing. However, it does not explicitly distinguish from the sibling tool list_traders, leaving some ambiguity.

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?

The description provides no guidance on when to use this tool versus alternatives like list_traders or get_trader. It lacks any contextual cues about use cases, prerequisites, or exclusion conditions, leaving the agent to infer the appropriate scenario.

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