Getting Started - Cover MCP (BETA)

Prerequisites

Before you begin:

1. Clone the Diffblue Cover MCP server repository https://github.com/diffblue/cover-mcp/

2. Install uv , a Python project manager tool from https://docs.astral.sh/uv/

3. Install Diffblue Cover CLI

Note Comprehensive documentation for setup and installation can be found in the README.md file in the Diffblue Cover MCP server repository https://github.com/diffblue/cover-mcp/.

Quick Installation

Option 1: Install globally for your AI tool

Choose your AI development environment:

For Claude Code: uv run fastmcp install claude-code --server-spec main.py

For Claude Desktop: uv run fastmcp install claude-desktop --server-spec main.py

For Cursor: uv run fastmcp install cursor --server-spec main.py

For Gemini CLI: uv run fastmcp install gemini-cli --server-spec main.py

Option 2: Install per-project

To generate a server configuration suitable for copy/pasting in to a mcp.json file, run uv run fastmcp unstall mcp-json --server-spec main .

"Diffblue Cover": {
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp",
    "fastmcp",
    "run",
    "/placeholder/path/to/cover-mcp/main.py"
  ]
}

Note The path placeholder paths used in these JSON snippets will depend on where you've cloned the Diffblue Cover MCP server repository.

Configuration

Add environment variables to customize the location your Diffblue Cover CLI installation:

"Diffblue Cover": {
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp",
    "fastmcp",
    "run",
    "/placeholder/path/to/cover-mcp/main.py"
  ],
  "env": {
    "DIFFBLUE_COVER_CLI": "/path/to/dcover"
  }
}

• DIFFBLUE_COVER_CLI: Custom path to dcover executable

If you want to supply additional CLI arguments to every invocation of dcover you can supply the DIFFBLUE_COVER_OPTIONS , for example (the complete configuration would look something like the following):

"Diffblue Cover": {
  "command": "uv",
  "args": [
    "run",
    "--with",
    "fastmcp",
    "fastmcp",
    "run",
    "/placeholder/path/to/cover-mcp/main.py"
  ],
  "env": {
    "DIFFBLUE_COVER_CLI": "/path/to/dcover",
    "DIFFBLUE_COVER_OPTIONS": "--verbose"
  }
}

Validating the MCP Server Configuration

The Diffblue MCP Server exposes tools, prompts, and resources to allow you to interact with Cover through AI applications. Your AI application should show you a list of tools, prompts, and resources available though the MCP connections.

Claude code, if configured and connected to the MCP server will show something like:

Diffblue Cover MCP Server

Status: ✔ connected
Command: uv
Args: run --with fastmcp fastmcp run /placeholder/path/to/cover-mcp/main.py
Config location: /path/to/project/.mcp.json
Capabilities: tools · resources · prompts
Tools: 1 tools

❯ 1. View tools
  2. Reconnect
  3. Disable

Using the MCP Server

From here you can instruct your AI application to "write unit tests for the java code contained in this project" to start dcover running across the whole project, for example. You can also provide specific classes or packages.