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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

predict_listing

Get the listing probability score for a crypto entity on Binance, Coinbase, or Upbit. Enter the entity slug to receive a Pro-tier prediction.

Instructions

Binance/Coinbase/Upbit listing probability score. Pro tier.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "entity_slug": "<entity_slug>"
    },
    "name": "predict_listing"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

C2.6/5.0
Behavior2/5

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

No annotations exist, so the description must disclose behavior. It mentions 'Pro tier' implying subscription requirement, but does not elaborate on data sources, update frequency, or whether predictions are real-time. This is minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely brief (6 words), sacrificing essential detail for brevity. While concise, it omits necessary context such as parameter explanation and output format.

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?

Given the lack of output schema and low parameter explanation, the description is incomplete. It does not specify the return value (e.g., probability percentage, score range) or handling of invalid slugs, leaving significant gaps for execution.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'entity_slug' is not explained in the description. The schema provides constraints but no semantic meaning, and with 0% schema coverage, the description fails to clarify what an entity slug is or how to format it (e.g., 'bitcoin').

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 tool provides listing probability scores for major exchanges (Binance, Coinbase, Upbit), specifying the output and scope. It distinctly identifies its purpose among siblings like 'submit_listing' or 'check_exploit_history'.

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?

No guidance is provided on when to use this tool versus alternatives, such as when to check for exchange listings via other tools. The description lacks context for proper tool selection.

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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