JSON Logs MCP Server

MCP server for Python JSON logs. That is what the json logs mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

A Model Context Protocol (MCP) server that enables Claude Desktop (or any MCP client) to read and analyze JSON-formatted log files. This server provides tools for searching, filtering, aggregating, and analyzing structured log data.

• 📁 Browse log files - List and read JSON-formatted log files
• 🔍 Search and filter - Query logs by level, module, function, message content, and time range
• 📊 Aggregate data - Group and analyze logs by various criteria
• 📈 Statistics - Get comprehensive statistics about your log data
• 🚀 Fast and efficient - Optimized for handling large log files

Getting it running

Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.

What it needs from you

Configuration is passed through the environment: MCP_JSON_LOGS_DIR. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

• Python 3.11 or higher - Claude Desktop (or another MCP client)

Things to watch

• It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
• Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

How it compares

Plenty of monitoring and observability servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by mfreeman451; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.