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<!-- ~ Copyright (c) 2025-2026 Datalayer, Inc. ~ ~ BSD 3-Clause License --> [](https://datalayer.io) [](https://github.com/sponsors/datalayer) # 🔧 MCP Codemode [](https://pypi.org/project/mcp-codemode) **Code Mode for MCP Tools**: Programmatically call and compose MCP tools through code execution instead of individual LLM tool calls. ## Overview MCP Codemode enables a "Code Mode" pattern where AI agents write Python code that orchestrates multiple MCP tool calls, rather than making individual tool calls through LLM inference. This approach is: - **More efficient**: Reduce LLM calls for multi-step operations - **More reliable**: Use try/except for robust error handling - **More powerful**: Parallel execution with asyncio, loops, conditionals - **More composable**: Save reusable patterns as skills ## Configuration highlights - **Direct tool calls**: `allow_direct_tool_calls` (default: false). When false, `call_tool` is hidden and all execution flows through `execute_code`. - **Tool listing filters**: `list_tool_names` accepts `server`, `keywords`, and `limit` for fast, filtered discovery. - **Search rerank hook**: Provide an optional `tool_reranker` callable to reorder search results before they are returned (e.g., LLM-based rerankers). Falls back to registry order when not provided. - **Execution language**: `execute_code` runs Python inside the configured sandbox; import bindings from `generated.servers.<server_name>`. - **Safety cap**: `max_tool_calls` can limit the number of tool invocations per `execute_code` run. - **Tool examples**: tool discovery and details include `output_schema` and `input_examples` to improve parameter accuracy. - **Deferred tools**: tools may be marked `defer_loading` by…
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