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kukapay

crypto-projects-mcp

get_project_data

Retrieve detailed cryptocurrency project information using token symbols. Access raw JSON data from Mobula API for insights on specific tokens like BTC or ETH.

Instructions

Fetch cryptocurrency project data from Mobula API.

Args:
    token_symbol (str): The symbol of the cryptocurrency token (e.g., 'BTC', 'ETH')

Returns:
    dict: Raw JSON response from Mobula API containing project details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
token_symbolYes

Implementation Reference

  • main.py:11-33 (handler)
    The handler function for the 'get_project_data' tool, decorated with @mcp.tool() for registration. It fetches project data from the Mobula API using the provided token symbol, handles errors, and returns a JSON dict.
    @mcp.tool()
    async def get_project_data(token_symbol: str) -> dict:
        """
        Fetch cryptocurrency project data from Mobula API.
        
        Args:
            token_symbol (str): The symbol of the cryptocurrency token (e.g., 'BTC', 'ETH')
        
        Returns:
            dict: Raw JSON response from Mobula API containing project details
        """
        async with httpx.AsyncClient() as client:
            try:
                # Construct API URL with token symbol
                url = f"https://production-api.mobula.io/api/1/metadata?asset={token_symbol}"
                response = await client.get(url)
                response.raise_for_status()  # Raise exception for non-200 status
                return response.json()
            except httpx.HTTPStatusError as e:
                return {"error": f"API request failed: {str(e)}"}
            except Exception as e:
                return {"error": f"Unexpected error: {str(e)}"}
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the API source and return format, but lacks details on error handling, rate limits, authentication needs, or whether it's read-only/destructive. This leaves significant gaps for a tool interacting with an external API.

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?

The description is appropriately sized with three sentences: purpose, parameter explanation, and return value. It's front-loaded with the main action and avoids unnecessary details, though the structure could be slightly more polished.

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 no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the response structure beyond 'raw JSON', error cases, or API limitations, which is inadequate for a tool fetching external data.

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 description coverage is 0%, so the description must compensate. It adds meaning by explaining the parameter's purpose (cryptocurrency token symbol) and providing examples ('BTC', 'ETH'), which helps beyond the bare schema. However, it doesn't cover constraints like valid symbols or format details.

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 ('Fetch') and resource ('cryptocurrency project data from Mobula API'), making the purpose understandable. However, it doesn't differentiate from siblings since none exist, so it can't achieve the highest score for sibling distinction.

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, prerequisites, or context for its application. It only states what it does without usage instructions.

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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