The 'dynamic_mcp_tools' tool is a meta-tool that wraps dynamically fetched tools from other MCP servers. The source code shows only a conversion function (_mcp_tool_to_openai) and result extraction (_extract_text_from_result), but NO explicit tool registration with schema, name, or description visible in the provided code. The tool definition itself is inferred from the file path and docstring, not directly registered. Additionally, the tool has no input schema visible (conversion happens on fetched tools, not on this tool's own parameters), no parameter descriptions, and the description provided is generic. The implementation converts MCP tools to OpenAI format but does not define its own callable interface with proper schema.

• Explicitly register dynamic_mcp_tools as a callable tool with a complete JSON Schema input definition. Include parameters like 'server_id' (enum of available servers), 'tool_name' (string), and any required arguments for the target tool.
• Expand tool description to 100-200 characters explaining: 'Dynamically execute tools from connected MCP servers (stdio/SSE). Specify the server and tool name, then pass tool-specific parameters. Returns structured output from the target tool.'
• Add parameter descriptions for each input: 'server_id: The MCP server to target (e.g., "stdio_server_1", "sse_server_2")', 'tool_name: Name of the tool to execute on the target server', 'tool_params: Tool-specific parameters as a JSON object'.
• Replace silent error handling (return empty string on isError) with actionable error messages: 'Tool execution failed on server {server_id}: {error_message}. Check server logs or try a different tool.'
• Document the output schema: 'Returns a structured object with fields: success (boolean), result (any), error (string if failed), execution_time_ms (number)'. This lets LLMs plan downstream actions.

Inferred effective spec: 2025-06-18+.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry