exasearchagent_exa_web_search
Perform web searches to retrieve relevant results including titles, snippets, and URLs using Exa search. Ideal for gathering up-to-date information across the web, though limited for niche topics.
Instructions
Search for webpages related to a query using Exa search. This tool performs a web search and returns relevant results including titles, snippets, and URLs. It's useful for finding up-to-date information on any topic, but may fail to find information of niche topics such like small cap crypto projects. Use this when you need to gather information from across the web.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default: 10) | |
| search_term | Yes | The search term |
Implementation Reference
- mesh_mcp_server/server.py:300-319 (handler)MCP call_tool handler that dispatches any tool call (including exasearchagent_exa_web_search) to the execute_tool method by parsing the tool name to extract agent_id and tool_name.@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:163-223 (registration)Dynamically processes agent metadata and registers tools with names like '{agent_id.lower()}_{tool_name}' (e.g., 'exasearchagent_exa_web_search' for agent 'ExaSearchAgent' tool 'exa_web_search'), including schema from metadata.async def process_tool_metadata(self) -> Dict[str, Dict[str, Any]]: """Process agent metadata and extract tool information. Returns: Dictionary mapping tool IDs to tool information """ agents_metadata = await self.fetch_agent_metadata() tool_registry = {} # Log filtering status if self.supported_agents is not None: logger.info( f"Filtering tools using supported agent list ({len(self.supported_agents)} agents specified)" ) else: logger.info("Loading tools from all available agents (no filter applied)") for agent_id, agent_data in agents_metadata.items(): # Skip agents not in our supported list (if a list is specified) if ( self.supported_agents is not None and agent_id not in self.supported_agents ): continue # Process tools for this agent for tool in agent_data.get("tools", []): if tool.get("type") == "function": function_data = tool.get("function", {}) tool_name = function_data.get("name") 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, } # Log which agents contributed tools agents_with_tools = set(info["agent_id"] for info in tool_registry.values()) logger.info(f"Loaded tools from agents: {', '.join(sorted(agents_with_tools))}") logger.info(f"Successfully loaded {len(tool_registry)} tools") return tool_registry
- mesh_mcp_server/server.py:39-53 (registration)Default list of supported agents includes 'ExaSearchAgent', enabling its tools such as 'exa_web_search' to be registered as 'exasearchagent_exa_web_search'.# Default supported agents 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 actually executes the tool by calling the remote Mesh API with the agent_id and tool_name extracted from the MCP tool name.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
- mesh_mcp_server/server.py:200-214 (schema)Extracts input schema (parameters) from the remote agent tool metadata or provides a default empty object schema.# 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,