coingeckotokeninfoagent_get_tokens_by_category
Retrieve detailed cryptocurrency token data by category using the CoinGecko API. Access prices, market caps, trading volumes, and price changes sorted by user-defined parameters such as market cap or volume.
Instructions
Get a list of tokens within a specific category. This tool retrieves token data for all cryptocurrencies that belong to a particular category, including price, market cap, volume, and price changes.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| category_id | Yes | The CoinGecko category ID (e.g., 'layer-1') | |
| order | No | Sort order for tokens (default: market_cap_desc) | market_cap_desc |
| page | No | Page number (default: 1) | |
| per_page | No | Number of results per page (1-250, default: 100) | |
| vs_currency | No | The currency to show results in (default: usd) | usd |
Implementation Reference
- mesh_mcp_server/server.py:300-319 (handler)Generic MCP tool handler that parses the prefixed tool name (e.g., 'coingeckotokeninfoagent_get_tokens_by_category'), extracts agent_id and tool_name, proxies the execution to the remote Mesh API via execute_tool, and returns the result as TextContent.@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:193-216 (registration)Dynamic tool registration logic: constructs the exact tool name format '{agent_id.lower()}_{tool_name}' (matching 'coingeckotokeninfoagent_get_tokens_by_category') from remote metadata and stores schema, description in tool_registry used by MCP server.if not tool_name: continue # Create a unique tool ID tool_id = f"{agent_id.lower()}_{tool_name}" # Get parameters or create default schema parameters = function_data.get("parameters", {}) if not parameters: parameters = { "type": "object", "properties": {}, "required": [], } # Store tool info tool_registry[tool_id] = { "agent_id": agent_id, "tool_name": tool_name, "description": function_data.get("description", ""), "parameters": parameters, }
- mesh_mcp_server/server.py:288-298 (schema)MCP list_tools implementation that exposes the dynamically registered tools including their inputSchema from remote metadata.@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:40-53 (helper)Hardcoded list of supported agents that includes 'CoinGeckoTokenInfoAgent', enabling tools from this agent (prefix '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:224-262 (helper)Helper function that performs the actual remote API call to execute the tool on the specified agent, used by the handler.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