Log Analyzer MCP server

Log Analyzer MCP is a powerful Python-based toolkit designed to streamline log file analysis. It provides both a Command-Line Interface (CLI) and a Model-Context-Protocol (MCP) server to help you efficiently find insights in log files, whether you're debugging applications, monitoring test runs, or analyzing verbose log outputs.

Installation Options

Installing from PyPI

The simplest way to install Log Analyzer MCP is via pip:

pip install log-analyzer-mcp

This installs both the loganalyzer CLI tool and the MCP server package.

Installing from Local Build

If you need to install from a local build:

1. Build the package:

   hatch build
   

2. Install the local build:

   pip uninstall log-analyzer-mcp -y
   pip install dist/log_analyzer_mcp-<version>-py3-none-any.whl
   

   Replace <version> with the actual version number.

Using Log Analyzer MCP

You can use Log Analyzer MCP in two primary ways:

As a Command-Line Tool

The loganalyzer CLI provides direct analysis capabilities for log files and supports various operations including searching, filtering, and context display.

As an MCP Server

The MCP server integrates log analysis capabilities with compatible clients like Cursor for an AI-assisted experience. It enables:

• Test log summarization
• Execution of test runs with varying verbosity
• Targeted unit test execution
• On-demand code coverage report generation
• Advanced log searching with various filters

Configuring the MCP Server

Configuration is handled via environment variables or a .env file in your project root:

• Set variables like LOG_DIRECTORIES, LOG_PATTERNS_ERROR, LOG_CONTEXT_LINES_BEFORE, and LOG_CONTEXT_LINES_AFTER directly in your environment.
• Alternatively, create a .env file with these settings.

Running the MCP Server

Via an MCP Client (e.g., Cursor)

Configure your MCP client to launch the log-analyzer-mcp executable. For Cursor, you might use a configuration like this in .cursor/mcp.json:

{
  "mcpServers": {
    "log_analyzer_mcp_server_prod": {
      "command": "uvx",
      "args": [
        "log-analyzer-mcp"
      ],
      "env": {
        "PYTHONUNBUFFERED": "1",
        "PYTHONIOENCODING": "utf-8",
        "MCP_LOG_LEVEL": "INFO",
        // Additional configuration via environment variables
        // "LOG_DIRECTORIES": "[\"/path/to/your/app/logs\"]",
        // "LOG_PATTERNS_ERROR": "[\"Exception:.*\"]"
      }
    }
  }
}

Running Directly

You can also run the server directly using its entry point:

log-analyzer-mcp --transport http --port 8080

Or for stdio transport:

log-analyzer-mcp --transport stdio

Use log-analyzer-mcp --help to see all available options.

Server Features

The MCP server provides several powerful capabilities:

• Test Log Analysis: Summarize test logs with the analyze_tests command
• Test Execution: Run tests with varying verbosity levels
• Unit Test Execution: Execute specific unit tests via run_unit_test
• Coverage Reports: Generate code coverage reports with create_coverage_report
• Advanced Log Searching: Search logs by time, content, or position

Each of these capabilities can be accessed through compatible MCP clients or via direct API calls to the server.

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "log_analyzer_mcp_server_prod" '{"command":"uvx","args":["log-analyzer-mcp"],"env":{"PYTHONUNBUFFERED":"1","PYTHONIOENCODING":"utf-8","MCP_LOG_LEVEL":"INFO"}}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "log_analyzer_mcp_server_prod": {
            "command": "uvx",
            "args": [
                "log-analyzer-mcp"
            ],
            "env": {
                "PYTHONUNBUFFERED": "1",
                "PYTHONIOENCODING": "utf-8",
                "MCP_LOG_LEVEL": "INFO"
            }
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "log_analyzer_mcp_server_prod": {
            "command": "uvx",
            "args": [
                "log-analyzer-mcp"
            ],
            "env": {
                "PYTHONUNBUFFERED": "1",
                "PYTHONIOENCODING": "utf-8",
                "MCP_LOG_LEVEL": "INFO"
            }
        }
    }
}

3. Restart Claude Desktop for the changes to take effect