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SolarWinds Logs MCP Server

SolarWinds Logs MCP Server

by jakenuts

SolarWinds Logs MCP Server

A Model Context Protocol (MCP) server for accessing and visualizing SolarWinds Observability logs.

Note -

This server is currently incomplete as it does not support structured data search (a limitation of the REST API?). I'm uncertain if it also needs to accept a data center to use in the api endpoint calls. Will address both when time allows (needed it for a real work problem, have to fix that first)

Tools

search_logs

Search SolarWinds Observability logs with optional filtering

  • Takes search parameters including filter, time range, and pagination options

  • Returns formatted log entries with timestamps, hostnames, and messages

  • Supports advanced filtering by group, entity, and more

  • Default search range is the last 24 hours

visualize_logs

Generate a histogram json response for of log events

  • Formatted for Claude and canvas representations

  • Configurable time intervals (minute, hour, day)

  • Supports UTC or local time zones

  • Customizable query filters and time ranges

  • Default visualization range is the last 24 hours

Resources

  • URI Template: solarwinds://{query}/search

  • Returns log entries matching the specified query

  • Example: solarwinds://error/search

Related MCP server: Log Analyzer MCP Server

Installation

Optionally install from npm:

npm install -g mcp-solarwinds

Or clone and build from source:

git clone https://github.com/@jakenuts/mcp-solarwinds.git
cd mcp-solarwinds
npm install
npm run build

Or just use npx in your configurations

For Cline VSCode Extension

Add to %APPDATA%/Code - Insiders/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json:

{
  "mcpServers": {
    "solarwinds": {
      "command": "npx",
      "args": ["-y", "mcp-solarwinds"],
      "env": {
        "SOLARWINDS_API_TOKEN": "your-api-token"
      },
      "autoApprove": ["search_logs", "visualize_logs"]
    }
  }
}

For Claude Desktop

Add to the appropriate config file:

Windows: %APPDATA%/Claude/claude_desktop_config.json MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "solarwinds": {
      "command": "npx",
      "args": ["-y", "mcp-solarwinds"],
      "env": {
        "SOLARWINDS_API_TOKEN": "your-api-token"
      }
    }
  }
}

Special Windows Configuration

If you encounter the ENOENT spawn npx issue on Windows, use this alternative configuration that specifies the full paths:

{
  "mcpServers": {
    "solarwinds": {
      "command": "C:\\Users\\[username]\\AppData\\Roaming\\nvm\\[node-version]\\node.exe",
      "args": [
        "C:\\Users\\[username]\\AppData\\Roaming\\npm\\node_modules\\npm\\bin\\npx-cli.js",
        "-y",
        "mcp-solarwinds"
      ],
      "env": {
        "SOLARWINDS_API_TOKEN": "your-api-token"
      }
    }
  }
}

Configuration

The SolarWinds Observability MCP server requires an API token to authenticate with the SolarWinds Observability API.

Configuration Methods

There are multiple ways to provide the API token:

  1. MCP Settings Configuration (Recommended): Configure the token in your MCP settings file

  2. Environment Variable: Set the SOLARWINDS_API_TOKEN environment variable

  3. Local .env File (For Testing): Create a .env file in the project root with SOLARWINDS_API_TOKEN=your-token

For local testing, you can:

  1. Copy .env.example to .env and add your token

  2. Run the example script: node examples/local-test.js

Tool Usage Examples

search_logs

Basic search:

{
  "filter": "error"
}

Advanced search with time range and pagination:

{
  "filter": "error",
  "entityId": "web-server",
  "startTime": "2025-03-01T00:00:00Z",
  "endTime": "2025-03-05T23:59:59Z",
  "pageSize": 100,
  "direction": "backward"
}

visualize_logs

Basic histogram (ASCII chart):

{
  "filter": "error",
  "interval": "hour"
}

Advanced visualization (ASCII chart):

{
  "filter": "error",
  "entityId": "web-server",
  "startTime": "2025-03-01T00:00:00Z",
  "endTime": "2025-03-05T23:59:59Z",
  "interval": "day",
  "use_utc": true
}

Claude visualization (JSON format):

{
  "filter": "error",
  "interval": "hour",
  "format": "json"
}

The JSON format returns data that Claude can visualize as a chart:

{
  "timeRanges": ["12:02", "12:03", "12:04", "12:05", "12:06", "12:07", "12:08", "12:09"],
  "counts": [261, 47, 48, 48, 31, 262, 270, 33],
  "total": 1000,
  "queryParams": {
    "query": "error",
    "startTime": "2025-03-05T00:00:00.000Z",
    "endTime": "2025-03-05T23:59:59.000Z"
  }
}

Development

Install dependencies:

npm install

Build the server:

npm run build

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. The MCP Inspector provides helpful debugging tools:

npm run debug:inspector

This will provide a URL to access the inspector in your browser, where you can:

  • View all MCP messages

  • Inspect request/response payloads

  • Test tools interactively

  • Monitor server state

For local testing without the MCP framework:

# Create a .env file with your token
cp .env.example .env
# Edit .env to add your token
# Run the example script
node examples/local-test.js

Technical Details

  • Built with TypeScript and the MCP SDK

  • Uses axios for API communication

  • Supports ISO 8601 date formats for time ranges

  • Generates ASCII histograms for log visualization

  • Default search range: last 24 hours

  • Default page size: 50 logs

  • Supports multiple authentication methods

Available Tools

2 tools
search_logsC

Search SolarWinds Observability logs with optional filtering

Inputs: filter, group, entityId, startTime, +4 more.

visualize_logsC

Generate a histogram visualization of log events

Inputs: interval, startTime, endTime, filter, +5 more.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.1/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have clearly distinct purposes: one searches logs with filtering, and the other generates visualizations. There is no overlap in functionality, making it impossible to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (search_logs, visualize_logs) with the same naming style. This predictability helps agents understand the tool set structure easily.

    Tool Count2/5

    With only two tools, the server feels too thin for a logs domain, lacking essential operations like creating, updating, or deleting logs. This minimal set limits agent capabilities significantly.

    Completeness2/5

    The tool set is severely incomplete for logs management, missing core CRUD operations and lifecycle coverage. Agents can only search and visualize, with no ability to modify or manage log data, leading to dead ends in workflows.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

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