dap-mcp

What is dap-mcp? The dap-mcp is an implementation of the Model Context Protocol (MCP) designed to manage Debug Adapter Protocol (DAP) sessions, optimizing the context window of large language models to enhance debugging workflows. How to use dap-mcp? To use dap-mcp, install it via pip and run the server with a JSON configuration file specifying debugger settings and source directories. Example command: pip install dap-mcp followed by python -m dap_mcp --config config.json. Key features of dap-mcp? Integration with Debug Adapter Protocol for standardized debugging. Utilization of MCP to optimize context for debugging. Tools for setting, listing, and removing breakpoints, controlling execution, evaluating expressions, and viewing source code. Customizable settings through a JSON configuration file. Use cases of dap-mcp? Streamlining debugging processes in software development. Enhancing the debugging experience for large language models. Facilitating the integration of various DAP servers through configuration. FAQ from dap-mcp? What programming languages does dap-mcp support? dap-mcp is primarily designed for Python debugging but can be extended to support other languages through additional configurations. Is dap-mcp open source? Yes, dap-mcp is open source and contributions are welcome. How can I contribute to dap-mcp? You can contribute by forking the repository, creating a new branch, writing tests, and submitting a pull request.

As an MCP (Model Context Protocol) server, dap-mcp enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use dap-mcp, install it via pip and run the server with a JSON configuration file specifying debugger settings and source directories. Example command: pip install dap-mcp followed by python -m dap_mcp --config config.json. Key features of dap-mcp? Integration with Debug Adapter Protocol for standardized debugging. Utilization of MCP to optimize context for debugging. Tools for setting, listing, and removing breakpoints, controlling execution, evaluating expressions, and viewing source code. Customizable settings through a JSON configuration file. Use cases of dap-mcp? Streamlining debugging processes in software development. Enhancing the debugging experience for large language models. Facilitating the integration of various DAP servers through configuration. FAQ from dap-mcp? What programming languages does dap-mcp support? dap-mcp is primarily designed for Python debugging but can be extended to support other languages through additional configurations. Is dap-mcp open source? Yes, dap-mcp is open source and contributions are welcome. How can I contribute to dap-mcp? You can contribute by forking the repository, creating a new branch, writing tests, and submitting a pull request.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.