DebugBundle
MCP

MCP Server

Connect AI coding agents to DebugBundle via the Model Context Protocol.

The DebugBundle MCP server exposes debugging tools that AI agents (GitHub Copilot, Cursor, Cline, and others) can call directly. Instead of switching between your IDE and a dashboard, your agent can query incidents, retrieve bundles, manage tokens, and run reproductions inline.

What is MCP?

The Model Context Protocol is an open standard for connecting AI assistants to external tools. MCP servers expose typed tool definitions that agents discover and invoke during conversations.

DebugBundle implements an MCP server that wraps the same domain services used by the API and CLI, ensuring consistent behavior across all interfaces.

Supported Node.js versions: 22.x through 26.x.

Authentication

The MCP server supports three authentication modes:

ModeHow it WorksUse Case
LocalUses CLI auth state from ~/.debugbundle/auth.jsonDefault for local development
Environment tokenReads DEBUGBUNDLE_MEMBER_TOKEN from the MCP server environmentMarketplace-managed, remote, and headless clients
Bearer TokenPass bearerToken parameter on tool callsCI/CD, remote agents, headless environments

When running locally alongside the CLI, the MCP server automatically picks up your authenticated session. No additional configuration is required.

If the CLI is not authenticated yet, bootstrap it first with any of these paths:

debugbundle login
debugbundle login dbundle_mem_xxxxxxxxxxxx
debugbundle login --github
debugbundle login --github-device

debugbundle login with no flags opens an interactive chooser in a TTY. --github first tries an existing gh auth token for a fully headless agent flow, then falls back to GitHub device flow when browser approval is needed. Email-code signup and manual token creation remain available in the web app for users who do not use GitHub.

For remote, marketplace-managed, or headless environments, prefer setting the member token in the MCP server environment:

{
  "mcpServers": {
    "debugbundle": {
      "command": "npx",
      "args": ["@debugbundle/mcp"],
      "env": {
        "DEBUGBUNDLE_MEMBER_TOKEN": "dbundle_mem_a1b2c3d4..."
      }
    }
  }
}

Use DEBUGBUNDLE_API_URL in the same environment block only for self-hosted or non-production API hosts. Individual tool calls can still pass a member token as bearerToken:

{
  "tool": "list_incidents",
  "arguments": {
    "bearerToken": "dbundle_mem_a1b2c3d4...",
    "limit": 5
  }
}

The npm package ships MCP Registry metadata as server.json with server name com.debugbundle/mcp.

Configuration

VS Code (GitHub Copilot)

Add to your VS Code settings or .vscode/mcp.json:

{
  "mcp": {
    "servers": {
      "debugbundle": {
        "command": "npx",
        "args": ["@debugbundle/mcp"]
      }
    }
  }
}

Cursor

Add to your Cursor MCP configuration:

{
  "mcpServers": {
    "debugbundle": {
      "command": "npx",
      "args": ["@debugbundle/mcp"]
    }
  }
}

Generic MCP Client

Any MCP-compatible client can connect using stdio transport:

npx @debugbundle/mcp

The server communicates over stdin/stdout using the MCP JSON-RPC protocol.

Tool Categories

The MCP server provides approximately 95 tools organized into these categories:

CategoryToolsDescription
Setup & Diagnostics5Validate connectivity and local setup
Incident Retrieval7Query, inspect, and manage incidents
Token Management6Create and manage project/member tokens
Webhook Management7Configure webhook endpoints and deliveries
Alert Management4Create and manage alert rules
Weekly Reports4Generate and retrieve analysis reports
Services1List discovered services
Projects4Create, list, update, and delete projects
Health Checks8Manage hosted availability checks and retained status history
Probes3Activate, list, and deactivate debug probes
Capture Policy2Get and update capture policies
Billing5Manage subscriptions, trials, and capacity
Members6Manage project collaborators and invitations
Analysis1Deep incident analysis

See the MCP Tools Reference for the complete tool catalog with parameters, and MCP Workflows for practical agent workflow patterns.

Next Steps

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