Mesh Agent MCP Server

Instructions

Implementation Reference

• mesh_mcp_server/tool_server.py:392-409 (handler)

  Handler function that executes the tool by looking up agent and tool name from registry and calling the Mesh API execute_tool method. This handles 'coingeckotokeninfoagent_get_trending_coins'.
  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/tool_server.py:264-301 (registration)

  Code that dynamically registers tools by constructing tool_id as '{agent_id.lower()}_{tool_name}', loading schema from metadata, and storing in registry. This creates the 'coingeckotokeninfoagent_get_trending_coins' tool if configured.
  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 # Check if this tool is enabled based on configuration if not self.is_tool_enabled(agent_id, tool_name): logger.debug( f"Skipping tool {tool_name} for agent {agent_id} (not in config)" # noqa: E501 ) tools_skipped += 1 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, } tools_enabled += 1 logger.debug(f"Enabled tool: {tool_id}")
• mesh_mcp_server/tool_server.py:316-353 (helper)

  Helper function that performs the actual API call to the Mesh sequencer to execute the agent's 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)

  In server.py variant, the CoinGeckoTokenInfoAgent is explicitly listed as a supported agent, enabling its tools like get_trending_coins to be dynamically registered as coingeckotokeninfoagent_get_trending_coins.
  DEFAULT_AGENTS = [ "CoinGeckoTokenInfoAgent", "DexScreenerTokenInfoAgent", "ElfaTwitterIntelligenceAgent", "ExaSearchAgent", "TwitterInfoAgent", "AIXBTProjectInfoAgent", "EtherscanAgent", "EvmTokenInfoAgent", "FundingRateAgent", "UnifaiTokenAnalysisAgent", "YahooFinanceAgent", "ZerionWalletAnalysisAgent"
• mesh_mcp_server/tool_server.py:379-389 (registration)

  MCP list_tools handler that exposes the dynamically registered tools, including their schemas.
  @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() ]