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desk3
by desk3

get_token_circulating_supply

Retrieve token circulating and total supply data for cryptocurrency trading pairs to analyze market metrics and token distribution.

Instructions

Get token circulating supply and total supply information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTrading pair symbol (required), format BTC -> BTCUSDT, ETH -> ETHUSDT

Implementation Reference

  • The core handler function that makes an HTTP GET request to the Desk3 API endpoint for token circulating supply data given a symbol.
    async def get_token_circulating_supply(symbol: str) -> dict[str, Any]:
        """
        Get token circulating supply and total supply information.
        :param symbol: Trading pair symbol (required), format BTC -> BTCUSDT, ETH -> ETHUSDT
        :return: Token circulating supply and total supply information
        """
        url = 'https://mcp.desk3.io/v1/market/circulating'
        params = {'symbol': symbol}
        try:
            return request_api('get', url, params=params)
        except Exception as e:
            raise RuntimeError(f"Failed to fetch token circulating supply data: {e}")
  • JSON Schema defining the input parameters for the tool, requiring a 'symbol' string matching the pattern for trading pairs.
    inputSchema={
        "type": "object",
        "properties": {
            "symbol": {
                "type": "string",
                "description": "Trading pair symbol (required), format BTC -> BTCUSDT, ETH -> ETHUSDT",
                "examples": ["BTCUSDT", "ETHUSDT", "BNBUSDT"],
                "pattern": "^[A-Z0-9]+$"
            },
        },
        "required": ["symbol"],
    },
  • Registration of the tool in the MCP server's list_tools() handler, including name, description, and schema.
    types.Tool(
        name="get_token_circulating_supply",
        description="Get token circulating supply and total supply information",
        inputSchema={
            "type": "object",
            "properties": {
                "symbol": {
                    "type": "string",
                    "description": "Trading pair symbol (required), format BTC -> BTCUSDT, ETH -> ETHUSDT",
                    "examples": ["BTCUSDT", "ETHUSDT", "BNBUSDT"],
                    "pattern": "^[A-Z0-9]+$"
                },
            },
            "required": ["symbol"],
        },
    ),
  • Dispatch handler in MCP server's call_tool() that validates input, calls the core handler, formats response as JSON, and returns TextContent.
    case "get_token_circulating_supply":
        if not arguments or "symbol" not in arguments:
            raise ValueError("Missing required argument: symbol")
        symbol = arguments["symbol"]
        try:
            data = await get_token_circulating_supply(symbol=symbol)
            return [
                types.TextContent(
                    type="text",
                    text=json.dumps(data, indent=2),
                )
            ]
        except Exception as e:
            raise RuntimeError(f"Failed to fetch token circulating supply data: {e}")
  • Helper function used by the handler to make authenticated HTTP requests to the Desk3 API.
    def request_api(method: str, url: str, params: dict = None, data: dict = None) -> any:
        headers = {
            'Accepts': 'application/json',
            'X-DESK3_PRO_API_KEY': API_KEY,
        }
        try:
            logging.info(f"Requesting {method.upper()} {url} params={params} data={data}")
            if method.lower() == 'get':
                response = requests.get(url, headers=headers, params=params)
            elif method.lower() == 'post':
                response = requests.post(url, headers=headers, json=data)
            else:
                raise ValueError(f"Unsupported HTTP method: {method}")
            response.raise_for_status()
            logging.info(f"Response {response.status_code} for {url}")
            return json.loads(response.text)
        except Exception as e:
            logging.error(f"Error during {method.upper()} {url}: {e}")
            raise
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify data sources, update frequency, rate limits, authentication requirements, or error conditions. This leaves significant gaps for a tool that likely queries external APIs.

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?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple data retrieval tool and front-loads the essential information.

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

Completeness3/5

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

For a single-parameter read tool with no output schema, the description adequately covers the basic purpose. However, without annotations or output details, it lacks information about return format (e.g., numeric values, timestamps, units) and behavioral constraints that would be helpful for reliable agent usage.

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?

The schema has 100% description coverage, with the 'symbol' parameter well-documented in the schema itself (including format, examples, and pattern). The description adds no additional parameter information beyond what's in the schema, meeting the baseline for high schema coverage.

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 clearly states the action ('Get') and the resource ('token circulating supply and total supply information'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools that also retrieve token-related data (like get_token_price), which prevents a perfect score.

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. With sibling tools like get_token_price that also retrieve token data, there's no indication of when supply information is preferred over price information or other metrics, leaving usage context ambiguous.

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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