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@blockchainacademics/mcp

@blockchainacademics/mcp

Official
by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_ai_crypto_metrics

Retrieve on-chain and market metrics for AI-focused cryptocurrencies, including Bittensor, Ritual, and Prime Intellect.

Instructions

Bittensor subnets, Ritual, Prime Intellect. Starter tier.

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_crypto_metrics"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

C2.1/5.0
Behavior1/5

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

With no annotations, the description must disclose behavioral traits. It fails to mention whether the tool is read-only, what data is returned, or any side effects. The description is completely opaque on behavior.

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

Conciseness3/5

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

The description is extremely short (10 words) but not well-structured. It reads as a list rather than a coherent statement. While concise, it sacrifices informativeness needed for tool selection.

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 input or output schema and no annotations, the description is the sole source of context. It fails to explain what the metrics are, time ranges, format, or how the data is organized. This is incomplete for an AI agent to use correctly.

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 has zero parameters, and schema coverage is 100% (empty schema). Per guidelines, baseline for 0 parameters is 4, and the description does not need to add parameter info. However, it does not clarify what 'metrics' are returned, but that is covered under other dimensions.

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

Purpose2/5

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

The description lists specific projects (Bittensor subnets, Ritual, Prime Intellect) and a tier designation but does not state what action the tool performs. The tool name includes 'get' but the description lacks a verb, leaving the purpose ambiguous. It does not differentiate from sibling tools like get_ai_agent_tokens or get_depin_projects.

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 only mentions specific topics without context on appropriate use cases or exclusions.

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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