Log Analyzer Mcp
Let your agent parse, search, and pull errors out of local or pasted logs across many formats while you debug production without switching tools.
Overview
log-analyzer-mcp is an Operate-phase MCP server that parses, searches, and extracts errors from logs across 9+ formats via AI-powered analysis tools.
What is this MCP server?
- AI-powered log analysis exposed as MCP tools
- Parse, search, and extract errors across 9+ log formats
- PyPI package codesdevs-log-analyzer v0.4.2 with stdio transport
- Suited for incident triage and post-deploy smoke investigation
- Developer Tools / Monitoring category fit for agent-assisted debugging
- Supports 9+ log formats per server description
- Version 0.4.2 on PyPI
- Repository: github.com/Fato07/log-analyzer-mcp
Community signal: 5 GitHub stars.
What problem does it solve?
Production logs arrive in incompatible formats and huge files, so finding the actual error line eats hours when you are solo on-call.
Who is it for?
Builders debugging multi-format logs locally or from exports who want the agent to search and extract errors without standing up a full log platform.
Skip if: Teams that need live tailing, retention, metrics, and paging in one SaaS observability product with no local log files.
What do I get? / Deliverables
With the PyPI MCP server connected, your agent can analyze logs in-session and surface errors and patterns you can fix or ship as patches.
- Parsed log views and search results via MCP tools
- Extracted error lines and patterns for agent-led fixes
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Journey fit
Log forensics is core production ops—when something fails in the wild, builders need fast error extraction, not another dashboard tab. The errors subphase is where parsing stacks, grepping timelines, and isolating failure lines matter most; this server automates that via MCP tools.
How it compares
MCP log-analysis toolkit, not a hosted APM or a single static lint skill.
Common Questions / FAQ
Who is log-analyzer-mcp for?
Solo builders and developers who troubleshoot from log files or pasted output and want MCP tools for parse, search, and error extraction.
When should I use log-analyzer-mcp?
Use it during Operate errors work after incidents, failed deploys, or support tickets when you need fast analysis across heterogeneous log formats.
How do I add log-analyzer-mcp to my agent?
Install codesdevs-log-analyzer from PyPI (v0.4.2), add the stdio MCP server entry in your client config, and point tools at log paths or content per the GitHub README.