MCP Servers

log-ai-optimizer

Compresses log files into templates and statistics using Drain3, and exposes them to AI assistants via an MCP server for efficient log monitoring and anomaly detection.

Category

README

log-ai-optimizer

Compresses log files into templates + stats (via Drain3) and exposes them to Claude through an MCP server, so AI log monitoring reads compact stats instead of raw lines.

Install

python -m venv .venv
.venv/Scripts/activate        # or: source .venv/bin/activate
pip install -r requirements.txt
pip install -e . --no-deps

Configure

cp config.example.yaml config.yaml

Edit config.yaml: list the log file paths to tail, plus DB path and sampling caps.

Run

Start ingestion (tails files, mines templates, writes to SQLite — keep this running):

log-ai-optimizer ingest config.yaml

In a separate process, run the MCP query server (stdio transport):

log-ai-optimizer serve config.yaml

To use it from Claude Desktop/Code, add it as an MCP server pointing at that command, e.g.:

{
  "mcpServers": {
    "log-ai-optimizer": {
      "command": "log-ai-optimizer",
      "args": ["serve", "/path/to/config.yaml"]
    }
  }
}

MCP tools

list_sources() — sources with template/line counts
get_template_stats(source_id, since?) — templates sorted by count
get_anomalies(source_id, window_minutes) — templates new or spiking vs. prior window
drill_down(template_id, limit) — sample raw params for a template
search_templates(query, source_id?) — substring search over templates

Dev

pip install -r requirements-dev.txt
pip install -e . --no-deps
pytest

See log-compress-spec.md for the full design.

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