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research-mcp

research-mcp

by atlas-rwa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_token_supply

Read the total supply of an ERC-20 tokenized stock from Robinhood Chain at the current block to verify issuance and redemption. Input a ticker or contract address.

Instructions

Source of truth: read an ERC-20's total supply directly from Robinhood Chain JSON-RPC at the current block. Use to verify issuance and redemption of a tokenized stock. Accepts a ticker or contract address.

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": {
      "token": "<token>"
    },
    "name": "get_token_supply"
  }
}

Input Schema

NameRequiredDescriptionDefault
tokenYesTicker or ERC-20 contract address (0x...)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well by noting the tool reads 'directly from Robinhood Chain JSON-RPC at the current block,' implying a live, authoritative read rather than a cached value. It also labels itself as 'Source of truth,' setting expectations for accuracy.

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

Conciseness5/5

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

Three succinct sentences each serve a purpose: the first states the core function and data source, the second gives a concrete use case, and the third clarifies the accepted input. No wasted words.

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

Completeness4/5

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

For a simple single-parameter read tool, the description covers what it does, when to use it, and what input is expected. It does not explicitly describe the return format or error behavior, but given the simplicity and absence of an output schema, this is adequate.

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?

Schema coverage is 100% since the token property is described as 'Ticker or ERC-20 contract address (0x...)' and the description repeats this nearly verbatim. It adds minimal extra meaning beyond the schema, so baseline 3 applies.

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?

Clearly states the tool reads an ERC-20's total supply directly from Robinhood Chain JSON-RPC at the current block. This specific verb-resource combination differentiates it from siblings like get_token_holders or get_token_market.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides a use case: 'Use to verify issuance and redemption of a tokenized stock.' However, it does not explicitly mention when not to use it or name alternative tools for similar tasks, so it stops short of a full 5.

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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