Graylog MCP Server

Graylog MCP Server

An MCP server that gives AI assistants direct access to your Graylog logs -- search, aggregate, analyze, and cluster log data through natural language.

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README

🔍 Graylog MCP Server

An MCP server that gives AI assistants direct access to your Graylog logs -- search, aggregate, analyze, and cluster log data through natural language.

What It Does

This server exposes your Graylog instance(s) as MCP tools, so AI assistants like Claude, Cursor, and others can query logs on your behalf. Instead of context-switching to the Graylog UI, you describe what you're looking for and the assistant handles the rest.

25 tools covering:

  • Log search -- full-text and field-filtered queries with pagination, exact/fuzzy matching, and configurable field selection
  • Contextual analysis -- fetch surrounding messages around a specific log entry
  • Aggregations -- histograms, field statistics, and two-dimensional field-over-time breakdowns
  • Log clustering -- group similar messages into structural templates using Drain3, with persistent template libraries per connection
  • Events -- search Graylog events, list event definitions and notifications
  • Saved searches -- save, list, and reuse query configurations
  • Multi-connection -- switch between Graylog instances (e.g., nonprod vs prod) within one session
  • Stream & field discovery -- list streams, discover distinct field values

Prerequisites

Installation

Via npx (recommended)

No installation needed. Configure your MCP client to run:

{
  "mcpServers": {
    "graylog": {
      "command": "npx",
      "args": ["graylog-mcp-server"]
    }
  }
}

From source

git clone https://github.com/jagadeesh52423/graylog-mcp.git
cd graylog-mcp
npm install

Then point your MCP client to the local entry point:

{
  "mcpServers": {
    "graylog": {
      "command": "node",
      "args": ["/absolute/path/to/graylog-mcp/src/index.js"]
    }
  }
}

Configuration

Create ~/.graylog-mcp/config.json:

{
  "connections": {
    "nonprod": {
      "baseUrl": "http://graylog-nonprod:9000",
      "apiToken": "your_api_token"
    },
    "prod": {
      "baseUrl": "http://graylog-prod:9000",
      "apiToken": "your_prod_api_token",
      "defaultFields": ["timestamp", "message", "level", "source", "PODNAME"]
    }
  },
  "defaultFields": ["timestamp", "gl2_message_id", "source", "env", "level", "message", "logger_name"]
}
Option Scope Description
connections Root Named Graylog instances, each with baseUrl and apiToken
defaultFields Root Global default fields returned in search results
defaultFields Connection Per-connection override (takes priority over global)

If no defaultFields are set, all fields (*) are returned.

Override the config path with the GRAYLOG_CONFIG_PATH environment variable:

{
  "mcpServers": {
    "graylog": {
      "command": "npx",
      "args": ["graylog-mcp-server"],
      "env": {
        "GRAYLOG_CONFIG_PATH": "/path/to/custom/config.json"
      }
    }
  }
}

MCP Client Config Locations

Client Config file
Claude Code ~/.claude/mcp.json
Cursor ~/.cursor/mcp.json
Claude Desktop (macOS) ~/Library/Application Support/Claude/claude_desktop_config.json

Usage

Once connected, talk to your AI assistant naturally. Some examples:

Connect to nonprod and show me error logs from the last hour
What are the top error sources in production over the past 6 hours?
Show me a histogram of level 3 errors over the past day, broken down by hour
Cluster the last 1000 error messages and show me the top patterns
Show me the messages surrounding log ID 01KH5PDR893AZJQBYJJ87AQTW5

Time Ranges

Relative: 30m, 1h, 2d, 1w, 3M, 1y

Absolute: provide from/to as ISO timestamps (2024-01-15T09:00:00Z) or Unix millis.

Default is 15 minutes if unspecified.

Available Tools

Connection Management

Tool Description
list_connections List configured Graylog connections
use_connection Switch to a named connection

Log Search

Tool Description
fetch_graylog_messages Search logs with query, filters, time range, pagination
get_surrounding_messages Get messages around a specific log entry by ID or timestamp
list_streams List available Graylog streams
list_field_values Discover distinct values for a field (top N by count)

Aggregations

Tool Description
get_log_histogram Time-bucketed message counts
get_field_aggregation Group by field with metrics (count, sum, avg, min, max)
get_field_time_aggregation Two-dimensional: field values over time intervals
debug_histogram_query Debug helper for empty histogram results

Log Clustering

Tool Description
cluster_log_messages Group similar messages into structural templates (Drain3)
list_log_templates List learned templates for the active connection
delete_log_template Remove a template
rename_log_template Give a template a human-readable label
export_log_templates Export template library as JSON
import_log_templates Bulk import templates (merge or replace)

Templates are persisted at ~/.graylog-mcp/templates/<connection>.json and improve over time as more messages are clustered.

Events

Tool Description
search_events Search Graylog events with filters
get_event_definitions List event definitions
get_event_notifications List event notifications

Saved Searches

Tool Description
save_search Save a query configuration for reuse
list_saved_searches List all saved searches
get_saved_search Retrieve a saved search by name
delete_saved_search Delete a saved search

Project Structure

src/
├── index.js                          Server bootstrap and request routing
├── config.js                         Connection config and field defaults
├── query.js                          Query building and Graylog API client
├── tools.js                          Tool schema definitions (25 tools)
├── timerange.js                      Flexible time range parsing
├── aggregations.js                   Histogram, field stats, time-series
├── events.js                         Graylog events API
├── saved-searches.js                 Persistent saved search store
├── clustering/
│   ├── index.js                      Strategy registry
│   ├── preprocess.js                 Message normalization and tokenization
│   ├── formatter.js                  Cluster response formatting
│   ├── template-store.js             Per-connection template persistence
│   └── strategies/
│       └── drain3.js                 Drain3 log clustering algorithm
└── tools/
    ├── cluster-errors.js             cluster_log_messages handler
    └── template-mgmt.js              Template CRUD handlers

Adding a Clustering Algorithm

  1. Create src/clustering/strategies/<name>.js implementing hydrate, serialize, and cluster (see drain3.js)
  2. Register it in src/clustering/index.js
  3. Pass algorithm: "<name>" to cluster_log_messages

License

MIT

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