exasearchagent_exa_answer_question
Retrieve direct, concise answers to specific questions by leveraging Exa's answer API and analyzing web content. Ideal for factual queries without needing a list of search results.
Instructions
Get a direct answer to a question using Exa's answer API. This tool provides concise, factual answers to specific questions by searching and analyzing content from across the web. Use this when you need a direct answer to a specific question rather than a list of search results. It may fail to find information of niche topics such like small cap crypto projects.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | The question to answer |
Implementation Reference
- mesh_mcp_server/server.py:301-319 (handler)MCP handler that executes the tool named 'exasearchagent_exa_answer_question' by parsing the name to extract agent_id and tool_name, then proxying the call to the remote Mesh API.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:288-299 (registration)MCP registration of dynamic tools including 'exasearchagent_exa_answer_question', providing name, description, and input schema from remote agent 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:192-198 (registration)Code that constructs the tool ID 'exasearchagent_exa_answer_question' from agent_id 'ExaSearchAgent' and tool_name 'exa_answer_question' in metadata.tool_name = function_data.get("name") if not tool_name: continue # Create a unique tool ID tool_id = f"{agent_id.lower()}_{tool_name}"
- mesh_mcp_server/server.py:224-262 (helper)Core helper that performs the actual remote API call to execute the tool on the Mesh agent.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:40-52 (registration)Default list of supported agents includes 'ExaSearchAgent', which provides the 'exa_answer_question' tool used to form 'exasearchagent_exa_answer_question'.DEFAULT_AGENTS = [ "CoinGeckoTokenInfoAgent", "DexScreenerTokenInfoAgent", "ElfaTwitterIntelligenceAgent", "ExaSearchAgent", "TwitterInfoAgent", "AIXBTProjectInfoAgent", "EtherscanAgent", "EvmTokenInfoAgent", "FundingRateAgent", "UnifaiTokenAnalysisAgent", "YahooFinanceAgent", "ZerionWalletAnalysisAgent"