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@blockchainacademics/mcp

@blockchainacademics/mcp

Official
by blockchainacademics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_tokenomics

Retrieve tokenomics data including supply, emission, vesting, unlock cliffs, and circulating supply percentage. Combines multiple data points into one source, eliminating spreadsheet scraping.

Instructions

Supply, emission, vesting, unlock cliffs, circulating %. Pro tier. Single source replacing spreadsheet scraping.

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": "get_tokenomics"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits. It lists data fields but does not cover whether the operation is read-only, authentication requirements, rate limits, or side effects, leaving significant gaps.

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 and to the point, but it lacks sentence structure and fails to elaborate on essential details. It is concise at the expense of completeness.

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, annotations, and parameter documentation, the description is insufficient for an agent to fully understand the tool's behavior, return format, or prerequisites. It leaves too many unknowns.

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

Parameters2/5

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

The single parameter entity_slug has 0% schema documentation. The description adds no explanation or example for this parameter, failing to compensate for the schema gap. It only explains what data is returned.

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 lists key data fields (supply, emission, vesting, etc.) and positions the tool as a premium, comprehensive source, making its purpose clear. However, it does not explicitly state that it retrieves data, leaving the action implied by the tool name.

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 generate_tokenomics_model or get_defi_protocol. The mention of 'Pro tier' hints at a premium context but lacks explicit usage conditions.

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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