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bca-mcp

bca-mcp

by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_ai_agent_tokens

Track key AI agent tokens including Virtuals, ai16z, Aixbt, Griffain, and Zerebro. Get live data on AI agent token performance and market trends.

Instructions

AI agent tokens tracker: Virtuals, ai16z, Aixbt, Griffain, Zerebro.

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_ai_agent_tokens"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

C2/5.0
Behavior2/5

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

No annotations exist, and the description does not disclose behavioral traits such as read-only status, rate limits, data freshness, or whether the list of tokens is static. The word 'tracker' implies data retrieval but is insufficient.

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 short (one sentence) but sacrifices clarity for brevity. It lacks essential information and does not front-load the most critical purpose.

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

Completeness1/5

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

Given no output schema and simple input, the description is severely incomplete. It does not specify what the tool returns (e.g., token data points, IDs, prices), how the limit parameter affects output, or any behavior details.

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 only parameter (limit) has no description in the schema (0% coverage), and the tool description does not explain its purpose, effect, or relationship to results. The description adds no value beyond the parameter name and default.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies it as an 'AI agent tokens tracker' and lists examples (Virtuals, ai16z, etc.), giving a general purpose. However, it lacks specificity on what data is tracked (prices, market cap, etc.) and does not clearly differentiate from sibling tools like get_ai_crypto_metrics or get_token_holders.

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. The description does not mention conditions, prerequisites, or scenarios where this tool is preferred.

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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