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ymylive
by ymylive

get_global_market

Retrieve global cryptocurrency market statistics: total market cap, 24h volume, BTC/ETH dominance, and more. Use to answer macro questions like total market cap or dominance trends.

Instructions

Get global cryptocurrency market stats: total market cap, total 24h volume, BTC/ETH dominance.

Use for macro questions like "what's the total crypto market cap?", "is BTC dominance rising?", "how many coins exist?".

Returns: Object with data containing: - active_cryptocurrencies, upcoming_icos, ongoing_icos, ended_icos, markets - total_market_cap (mapping of currency -> amount) - total_volume (mapping of currency -> amount) - market_cap_percentage (per-coin share of total cap, e.g. {"btc": 52.1}) - market_cap_change_percentage_24h_usd - updated_at

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The actual tool handler for get_global_market. Decorated with @mcp.tool(), it calls _cg_get('/global') to fetch global crypto market stats from CoinGecko's /global endpoint.
    @mcp.tool()
    async def get_global_market() -> Any:
        """Get global cryptocurrency market stats: total market cap, total 24h volume, BTC/ETH dominance.
    
        Use for macro questions like "what's the total crypto market cap?",
        "is BTC dominance rising?", "how many coins exist?".
    
        Returns:
            Object with `data` containing:
              - active_cryptocurrencies, upcoming_icos, ongoing_icos, ended_icos, markets
              - total_market_cap (mapping of currency -> amount)
              - total_volume     (mapping of currency -> amount)
              - market_cap_percentage (per-coin share of total cap, e.g. {"btc": 52.1})
              - market_cap_change_percentage_24h_usd
              - updated_at
        """
        return await _cg_get("/global")
  • The _cg_get helper function used by the handler. Constructs the full CoinGecko API URL using the base URL (pro or public) and appends headers.
    async def _cg_get(path: str, params: dict[str, Any] | None = None) -> Any:
        return await _http_get(
            f"{_coingecko_base()}{path}",
            params=params,
            headers=_coingecko_headers(),
        )
  • The tool is registered via the @mcp.tool() decorator on the get_global_market function. The 'mcp' object is imported from coin_mcp.core.
    @mcp.tool()
    async def get_global_market() -> Any:
  • The mcp FastMCP instance imported by the tool module. Defined in coin_mcp/core.py at line 58.
    """coin-mcp core — FastMCP instance, configuration, and shared helpers.
Behavior4/5

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

No annotations provided, so description carries full burden. It describes the return structure in detail and implies a read-only operation. No contradictions or missing behavioral traits.

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

Conciseness4/5

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

Well-structured with bullet points and example questions. Slightly verbose but each sentence adds value. No wasted words.

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

Completeness5/5

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

Given no output schema, description fully explains return fields. No annotations but description compensates completely. Tool is simple (no params) and description is sufficient.

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?

No parameters defined, so schema coverage is 100%. Description adds meaning beyond schema by detailing the structure of the returned data object.

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?

Description clearly states the tool gets global cryptocurrency market stats, listing specific fields like total market cap and BTC/ETH dominance. It distinguishes from sibling tools by focusing on macro-level data.

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?

Provides example use cases ('macro questions') but does not explicitly state when not to use or mention alternatives. However, the context is clear enough for an agent to decide.

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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