GDB MCP Server Integration

What does “GDB” MCP Server do?

The GDB MCP Server is a specialized server implementing the Model Context Protocol (MCP) that exposes the debugging capabilities of GDB (GNU Debugger) to AI assistants and other clients. By acting as a bridge between AI agents and GDB, it enables intelligent assistants to create, manage, and interact with remote debugging sessions programmatically. This integration empowers developers to automate debugging workflows, set and manipulate breakpoints, inspect stack frames and variables, and control program execution—all via standardized MCP tools. With support for concurrent multi-session debugging and both standard input/output and server-sent events transports, the GDB MCP Server is a powerful tool for enhancing software development, debugging, and code analysis through AI-driven automation.

List of Prompts

No prompt templates are explicitly documented in the repository.

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List of Resources

No explicit MCP resources are documented in the repository.

List of Tools

• Session Management

  • create_session: Create a new GDB debugging session.
  • get_session: Retrieve information about a specific session.
  • get_all_sessions: List all active debugging sessions.
  • close_session: Terminate a debugging session.

• Debug Control

  • start_debugging: Start the debugging process.
  • stop_debugging: Stop the current debugging session.
  • continue_execution: Resume program execution after a pause/breakpoint.
  • step_execution: Step into the next line of code.
  • next_execution: Step over to the next line without entering functions.

• Breakpoint Management

  • get_breakpoints: List all active breakpoints.
  • set_breakpoint: Add a new breakpoint.
  • delete_breakpoint: Remove an existing breakpoint.

• Debug Information

  • get_stack_frames: Retrieve current stack frame information.
  • get_local_variables: List local variables in the current context.
  • get_registers: Fetch CPU register values.
  • read_memory: Read contents from the program’s memory.

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Use Cases of this MCP Server

• Automated Remote Debugging
  • AI agents can programmatically create, manage, and close multiple GDB sessions for complex software projects, facilitating automated bug detection and resolution.
• Breakpoint Management via AI
  • Assistants can dynamically set, list, and remove breakpoints based on code analysis or user instructions, streamlining the debugging workflow.
• Real-time Variable Inspection
  • Developers can use AI to fetch stack frames, local variables, and register values during execution, enhancing code understanding and error tracing.
• Memory Analysis Automation
  • The server allows AI to read specific memory locations, enabling automated memory checks, buffer analysis, or forensic tasks.
• Multi-session Debugging
  • Supports concurrent debugging of several sessions, making it ideal for large-scale, multi-component systems or teaching environments.

How to set it up

Windsurf

1. Prerequisites: Ensure you have the GDB MCP Server binary or have built it from source.
2. Configuration File: Open your Windsurf configuration file.
3. Add MCP Server: Insert the following JSON snippet in your mcpServers section:

   {
     "gdb-mcp": {
       "command": "./mcp-server-gdb",
       "args": [],
       "transport": "streamable_http"
     }
   }
   

4. Save & Restart: Save the configuration and restart Windsurf.
5. Verify: Check if the GDB MCP Server appears in the interface.

Claude

1. Prerequisites: Download or build the GDB MCP Server.
2. Configuration File: Locate your Claude MCP configuration.
3. Add MCP Server:

   {
     "gdb-mcp": {
       "command": "./mcp-server-gdb",
       "args": [],
       "transport": "streamable_http"
     }
   }
   

4. Save & Restart: Apply changes and restart Claude.
5. Verify: Ensure the server is accessible in Claude.

Cursor

1. Prerequisites: Obtain the GDB MCP Server binary.
2. Edit Configuration: Open Cursor’s settings for MCP servers.
3. Insert Configuration:

   {
     "gdb-mcp": {
       "command": "./mcp-server-gdb",
       "args": [],
       "transport": "streamable_http"
     }
   }
   

4. Save & Restart: Save and restart Cursor.
5. Verification: Confirm the server is listed in Cursor.

Cline

1. Prerequisites: Download or build GDB MCP Server.
2. Find Config File: Open Cline’s configuration for MCP servers.
3. Add Server Entry:

   {
     "gdb-mcp": {
       "command": "./mcp-server-gdb",
       "args": [],
       "transport": "streamable_http"
     }
   }
   

4. Save & Restart: Make changes effective by saving and restarting.
5. Verify: Check the connection to GDB MCP Server.

Securing API Keys using Environment Variables If the server requires API keys (not specified in this repo), use environment variables. Example:

{
  "gdb-mcp": {
    "command": "./mcp-server-gdb",
    "args": [],
    "env": {
      "API_KEY": "${GDB_MCP_API_KEY}"
    },
    "inputs": {
      "api_key": "${GDB_MCP_API_KEY}"
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "gdb-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “gdb-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the documentation and feature set, the GDB MCP Server provides a comprehensive set of debugging tools but lacks explicit prompt templates and documented resources. Sampling and Roots support are not specified. Given strong tool support, open-source license, and clear use cases, the overall utility is solid for developers seeking AI-driven GDB automation.

MCP Score