coingeckotokeninfoagent_get_category_data
Retrieve market data for cryptocurrency categories from CoinGecko, including market cap, volume, top coins, and price changes, to analyze and monitor crypto trends efficiently.
Instructions
Get market data for all cryptocurrency categories from CoinGecko. This tool retrieves comprehensive information about all categories including market cap, volume, market cap change, top coins in each category, and more.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| order | No | Sort order for categories (default: market_cap_desc) |
Implementation Reference
- mesh_mcp_server/server.py:40-52 (registration)Default list of supported agents includes "CoinGeckoTokenInfoAgent" enabling tools prefixed with "coingeckotokeninfoagent_" such as the target tool.DEFAULT_AGENTS = [ "CoinGeckoTokenInfoAgent", "DexScreenerTokenInfoAgent", "ElfaTwitterIntelligenceAgent", "ExaSearchAgent", "TwitterInfoAgent", "AIXBTProjectInfoAgent", "EtherscanAgent", "EvmTokenInfoAgent", "FundingRateAgent", "UnifaiTokenAnalysisAgent", "YahooFinanceAgent", "ZerionWalletAnalysisAgent"
- mesh_mcp_server/server.py:195-199 (registration)Dynamic registration of tools where tool ID is constructed as lowercase agent ID + "_" + tool name, e.g. "coingeckotokeninfoagent_get_category_data".continue # Create a unique tool ID tool_id = f"{agent_id.lower()}_{tool_name}"
- mesh_mcp_server/server.py:288-298 (schema)MCP tool listing that provides schema (inputSchema from metadata) for each registered tool including the target.@app.list_tools() async def list_tools() -> List[types.Tool]: """List all available tools.""" return [ types.Tool( name=tool_id, description=tool_info["description"], inputSchema=tool_info["parameters"], ) for tool_id, tool_info in self.tool_registry.items() ]
- mesh_mcp_server/server.py:300-319 (handler)Generic handler for all proxied tools: looks up registry entry for tool name, extracts agent and tool details, calls execute_tool to proxy to external Mesh API.@app.call_tool() async def call_tool(name: str, arguments: dict) -> List[types.TextContent]: """Call the specified tool with the given arguments.""" try: if name not in self.tool_registry: raise ValueError(f"Unknown tool: {name}") tool_info = self.tool_registry[name] result = await self.execute_tool( agent_id=tool_info["agent_id"], tool_name=tool_info["tool_name"], tool_arguments=arguments, ) # Convert result to TextContent return [types.TextContent(type="text", text=str(result))] except Exception as e: logger.error(f"Error calling tool {name}: {e}") raise ValueError(f"Failed to call tool {name}: {str(e)}") from e
- mesh_mcp_server/server.py:224-262 (helper)Helper function that proxies tool execution to the external Mesh API endpoint using POST /mesh_request with agent_id, tool name, and arguments.async def execute_tool( self, agent_id: str, tool_name: str, tool_arguments: Dict[str, Any] ) -> Dict[str, Any]: """Execute a tool on a mesh agent. Args: agent_id: ID of the agent to execute the tool on tool_name: Name of the tool to execute tool_arguments: Arguments to pass to the tool Returns: Tool execution result Raises: ToolExecutionError: If there's an error executing the tool """ request_data = { "agent_id": agent_id, "input": {"tool": tool_name, "tool_arguments": tool_arguments}, } # Add API key if available if Config.HEURIST_API_KEY: request_data["api_key"] = Config.HEURIST_API_KEY try: result = await call_mesh_api( "mesh_request", method="POST", json=request_data ) return result.get("data", result) # Prefer the 'data' field if it exists except MeshApiError as e: # Re-raise API errors with clearer context raise ToolExecutionError(str(e)) from e except Exception as e: logger.error(f"Error calling {agent_id} tool {tool_name}: {e}") raise ToolExecutionError( f"Failed to call {agent_id} tool {tool_name}: {str(e)}" ) from e