Skip to main content

MCP server and tools for analyzing test and runtime logs.

Project description

Log Analyzer MCP

CI codecov PyPI - Version

Overview: Analyze Logs with Ease

Log Analyzer MCP is a powerful Python-based toolkit designed to streamline the way you interact with log files. Whether you're debugging complex applications, monitoring test runs, or simply trying to make sense of verbose log outputs, this tool provides both a Command-Line Interface (CLI) and a Model-Context-Protocol (MCP) server to help you find the insights you need, quickly and efficiently.

Why use Log Analyzer MCP?

  • Simplify Log Analysis: Cut through the noise with flexible parsing, advanced filtering (time-based, content, positional), and configurable context display.
  • Integrate with Your Workflow: Use it as a standalone loganalyzer CLI tool for scripting and direct analysis, or integrate the MCP server with compatible clients like Cursor for an AI-assisted experience.
  • Extensible and Configurable: Define custom log sources, patterns, and search scopes to tailor the analysis to your specific needs.

Key Features

  • Core Log Analysis Engine: Robust backend for parsing and searching various log formats.
  • loganalyzer CLI: Intuitive command-line tool for direct log interaction.
  • MCP Server: Exposes log analysis capabilities to MCP clients, enabling features like:
    • Test log summarization (analyze_tests).
    • Execution of test runs with varying verbosity.
    • Targeted unit test execution (run_unit_test).
    • On-demand code coverage report generation (create_coverage_report).
    • Advanced log searching: all records, time-based, first/last N records.
  • Hatch Integration: For easy development, testing, and dependency management.

Getting Started: Using Log Analyzer MCP

There are two primary ways to use Log Analyzer MCP:

  1. As a Command-Line Tool (loganalyzer):

    • Ideal for direct analysis, scripting, or quick checks.
    • Requires Python 3.9+.
    • For installation and usage, please see the Getting Started Guide.
  2. As an MCP Server (e.g., with Cursor):

    • Integrates log analysis capabilities directly into your AI-assisted development environment.
    • To install and configure the MCP server for use in a client like Cursor, follow the instructions below.

Installing the MCP Server for Client Integration

To integrate the Log Analyzer MCP server with a client application (like Cursor), you'll typically configure the client to launch the log-analyzer-mcp package, which is available on PyPI.

Example Client Configuration (e.g., in .cursor/mcp.json):

{
  "mcpServers": {
    "log_analyzer_mcp_server_prod": {
      "command": "uvx", // uvx is a tool to run python executables from venvs
      "args": [
        "log-analyzer-mcp" // Fetches and runs the latest version from PyPI
        // Or, for a specific version: "log-analyzer-mcp==0.2.0"
      ],
      "env": {
        "PYTHONUNBUFFERED": "1",
        "PYTHONIOENCODING": "utf-8",
        "MCP_LOG_LEVEL": "INFO", // Recommended for production
        // "MCP_LOG_FILE": "/path/to/your/logs/mcp/log_analyzer_mcp_server.log", // Optional
        // --- Configure Log Analyzer specific settings via environment variables ---
        // Example: "LOG_DIRECTORIES": "[\"/path/to/your/app/logs\"]",
        // Example: "LOG_PATTERNS_ERROR": "[\"Exception:.*\"]"
        // (Refer to docs/configuration.md (once created) for all options)
      }
    }
    // You can add other MCP servers here
  }
}

Notes:

  • Replace placeholder paths and consult the Getting Started Guide and Developer Guide for more on configuration options and environment variables.
  • The actual package name on PyPI is log-analyzer-mcp.

Documentation

  • API Reference: Detailed reference for MCP server tools and CLI commands.
  • Getting Started Guide: For users and integrators.
  • Developer Guide: For contributors and those building from source.
  • Refactoring Plan: Technical details on the ongoing evolution of the project.
  • (Upcoming) Configuration Guide: Detailed explanation of all .env and environment variable settings.
  • (Upcoming) CLI Usage Guide: Comprehensive guide to all loganalyzer commands and options.

Contributing

We welcome contributions! Please see CONTRIBUTING.md and the Developer Guide for guidelines on how to set up your environment, test, and contribute.

License

Log Analyzer MCP is licensed under the MIT License with Commons Clause. See LICENSE.md for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

log_analyzer_mcp-0.1.6.tar.gz (110.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

log_analyzer_mcp-0.1.6-py3-none-any.whl (39.1 kB view details)

Uploaded Python 3

File details

Details for the file log_analyzer_mcp-0.1.6.tar.gz.

File metadata

  • Download URL: log_analyzer_mcp-0.1.6.tar.gz
  • Upload date:
  • Size: 110.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.28.1

File hashes

Hashes for log_analyzer_mcp-0.1.6.tar.gz
Algorithm Hash digest
SHA256 6e191e15cbf051940a7de73f52738c8b01d96d9120b15bf358fc7796ba2c33ad
MD5 d7df400dc70454a8b58f93eda5cc11f3
BLAKE2b-256 53b719cb48f8b68b5aa7e5b2103d65421bbb99f3499877bcb4f2b40de58bfa53

See more details on using hashes here.

File details

Details for the file log_analyzer_mcp-0.1.6-py3-none-any.whl.

File metadata

File hashes

Hashes for log_analyzer_mcp-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 86cea0afd1797811565ddd3f1b52bca6bdf07a6626e5a47d8565c70ade36e220
MD5 d2bc08daff93ba9d459dd1c64ddd2009
BLAKE2b-256 fbd15d93d0d0b9e996e61240055f34d4167c299fc345d323d1dc0396d8ecba02

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page