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MCP Jacoco Reporter

@crisschan

Repository

Basic information

Category

Other

Transports

stdio

Author

crisschan

Submitted by

Criss Chen

About MCP Jacoco Reporter

No overview available yet

#mcp-jacoco#code-coverage#ai-integration

MCP Jacoco Reporter config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-jacoco-reporter-server": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/Users/crisschan/workspace/pyspace/mcp-jacoco-reporter/mcp-jacoco-reporter-server.py"
      ],
      "env": {
        "COVERED_TYPES": "nocovered, partiallycovered, fullcovered"
      },
      "alwaysAllow": [
        "jacoco_reporter_server"
      ]
    }
  }
}

MCP Jacoco Reporter tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Mcp Jacoco Reporter?

Mcp Jacoco Reporter is a server tool that converts JaCoCo code coverage reports into JSON formats optimized for Large Language Models (LLMs). It is designed for development teams who want to use AI tools to analyze, summarize, and act on Java code coverage data more effectively.

How to use Mcp Jacoco Reporter?

Install the server using uv with the provided MCP configuration, which includes an environment variable to filter coverage types. The server exposes a single tool, jacoco_reporter_server, which takes a path to a JaCoCo XML report and returns coverage metrics as structured JSON.

Key features of Mcp Jacoco Reporter

  • Smart conversion of JaCoCo XML into LLM-friendly JSON format.
  • Supports multiple coverage types (instruction, branch, line, etc.).
  • Fast and lightweight report processing.
  • Well-organized JSON output for easy AI consumption.
  • Filter coverage data by specific metrics of interest.

Use cases of Mcp Jacoco Reporter

  • Generate quick, AI-readable summaries of code coverage for pull reviews.
  • Automatically identify untested or poorly tested source files and branches.
  • Feed structured coverage data into LLMs for smart test case suggestions.
  • Enable AI-assisted test planning and coverage gap analysis.
  • Automate documentation of coverage results for team dashboards.

Frequently asked questions

1

What format does Mcp Jacoco Reporter output?

The server converts JaCoCo XML reports into a structured JSON array, where each entry includes source file, package, and breakdowns of uncovered and partially covered lines and branches.

2

How do I install Mcp Jacoco Reporter?

It is installed via `uv` by adding the provided JSON block to your MCP configuration. The block specifies the command, arguments, environment variable `COVERED_TYPES`, and the tool to always allow.

3

What input is required to run the tool?

The `jacoco_reporter_server` tool requires the `jacoco_report_path` argument, which is the filesystem path to the JaCoCo XML report.

4

Does Mcp Jacoco Reporter depend on a specific runtime?

Yes, it requires the `uv` package manager and the `mcp[cli]` Python package to be available in the execution environment.

5

Can I limit which coverage types are analyzed?

Yes. The `COVERED_TYPES` environment variable in the configuration lets you filter the report by coverage statuses such as `nocovered`, `partiallycovered`, and `fullcovered`.

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