Log Analyzer MCP

Name: Log Analyzer MCP
Author: Fato07

by Fato07version 0.4.2i★ –iRuns on your computer

Registry nameio.github.Fato07/log-analyzer-mcp

Install

Overview

Description from the maker (original English)

AI-powered log analysis - parse, search, extract errors across 9+ formats

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "log-analyzer": {
      "command": "uvx",
      "args": [
        "codesdevs-log-analyzer"
      ]
    }
  }
}

Run this in your terminal

claude mcp add log-analyzer -- uvx codesdevs-log-analyzer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "log-analyzer": {
      "command": "uvx",
      "args": [
        "codesdevs-log-analyzer"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "log-analyzer": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "codesdevs-log-analyzer"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Fato07, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7259 servers in this category
Published to the registry more recently than 2% of the other 7259 servers in this category
Basic checks equal to or better than 100% of the other 7259 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Log Analyzer MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.2) reached the registry 10 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Log Analyzer MCP

🔍 Stop copy-pasting logs into AI. Let Claude read them directly.

An MCP server for AI-powered log analysis. Parse, search, and debug log files across 9+ formats — right from Claude Code.

📊 At a Glance


14 MCP tools	9+ log formats
280 tests	81%+ coverage

🎬 Demo

*Analyzing logs with 14 specialized tools*

🤔 Why?

Without log-analyzer-mcp	With log-analyzer-mcp
Copy-paste chunks of logs	Point Claude at the file
Lose context between pastes	Full file access
Manual format parsing	Auto-detection
Miss related errors	Smart correlation

✨ Features

Auto-Detection — Identifies format from 9+ common log types
Smart Search — Pattern matching with context, regex, and time filtering
Error Extraction — Groups similar errors, captures stack traces
Natural Language — Ask questions like "what errors happened today?"
Sensitive Data Scan — Detect PII, credentials, and secrets
Multi-File Analysis — Correlate events across distributed systems
Streaming — Handles 1GB+ files without memory issues

🚀 Quick Start

# Install (adds to Claude Code automatically)

uvx codesdevs-log-analyzer install

Then in Claude Code:

Analyze /var/log/app.log and tell me what's causing the errors

📦 Installation

One-liner (Recommended)

uvx codesdevs-log-analyzer install

Manual

pip / uv / Claude Code config

# pip

pip install codesdevs-log-analyzer

uv

uv tool install codesdevs-log-analyzer

Add to ~/.claude/settings.json:

"mcpServers": { "log-analyzer": { "command": "uvx", "args": ["codesdevs-log-analyzer"] } } }

📋 Supported Formats

Format	Example
Syslog	`Jan 15 10:30:00 hostname process[pid]: message`
Apache/Nginx	`127.0.0.1 - - [15/Jan/2026:10:30:00] "GET /path" 200`
JSON Lines	`{"timestamp": "...", "level": "ERROR", "message": "..."}`
Docker	`2026-01-15T10:30:00.123Z stdout message`
Python	`2026-01-15 10:30:00,123 - module - ERROR - message`
Java/Log4j	`2026-01-15 10:30:00,123 ERROR [thread] class - message`
Kubernetes	`level=error msg="..." ts=2026-01-15T10:30:00Z`
Generic	Any line with recognizable timestamp

⚡ Performance

Metric	Value
100MB log file	< 10 seconds
Memory footprint	Streaming (no full load)
Max tested size	1GB+
Format detection	< 100ms

🛠️ Available Tools

Tool	Description
`log_analyzer_parse`	Detect format and extract metadata
`log_analyzer_search`	Search with context lines
`log_analyzer_extract_errors`	Extract and group errors
`log_analyzer_summarize`	Generate debugging summary
`log_analyzer_correlate`	Find related events
`log_analyzer_watch`	Monitor for new entries
`log_analyzer_ask`	Natural language queries
`log_analyzer_scan_sensitive`	Detect PII/credentials
+ 6 more	Full reference →

💡 Examples

Find errors:

Extract all errors from /var/log/app.log, group similar ones

Search with context:

Search for "timeout" in app.log with 5 lines of context

Correlate events:

What happened 60 seconds before each OutOfMemoryError?

Scan for secrets:

Check /var/log/app.log for accidentally logged credentials

🔧 Development

git clone https://github.com/Fato07/log-analyzer-mcp

cd log-analyzer-mcp uv sync uv run pytest -v --cov

📈 Star History

📄 License

MIT License - see LICENSE for details.

Found this useful? Give it a ⭐ on GitHub!

Report bugs · Request features · Discussions · Full docs

Built by Fato07 at CodesDevs

Log Analyzer MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Log Analyzer MCP

📊 At a Glance

🎬 Demo

🤔 Why?

✨ Features

🚀 Quick Start

📦 Installation

One-liner (Recommended)

Manual

uv

📋 Supported Formats

⚡ Performance

🛠️ Available Tools

💡 Examples

🔧 Development

📈 Star History

📄 License