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otelcol-mcp

MCP.Pizza Chef: mottibec

otelcol-mcp is an MCP server that enables dynamic configuration of OpenTelemetry Collectors. It manages receivers, processors, and exporters, allowing users to add, remove, and configure these components in real time. It also provides tools to update local resource files with the latest component metadata from GitHub, facilitating seamless observability pipeline management.

Use This MCP server To

Dynamically configure OpenTelemetry Collectors via MCP tools Manage OpenTelemetry receivers, processors, and exporters centrally Update local component metadata from GitHub automatically Retrieve detailed metadata about OpenTelemetry components Integrate OpenTelemetry configuration into AI-driven workflows Automate observability pipeline adjustments based on real-time data

README

OpenTelemetry Collector MCP Server

An MCP server implementation for configuring OpenTelemetry Collectors.

Features

  • Dynamic OpenTelemetry Configuration: Configure OpenTelemetry Collectors through MCP tools
  • Component Management: Add, remove, and configure receivers, processors, and exporters

Tools

  • Update Resources
    • Updates local resource files with the latest component information from GitHub
    • No input parameters required
    • Returns statistics about updated components (receivers, processors, exporters)

Resources

  • Receivers (receivers://receivers)

    • Lists all available OpenTelemetry receivers
    • Returns receiver metadata including name, description, and stability
  • Processors (processors://processors)

    • Lists all available OpenTelemetry processors
    • Returns processor metadata including name, description, and stability
  • Exporters (exporters://exporters)

    • Lists all available OpenTelemetry exporters
    • Returns exporter metadata including name, description, and stability
  • Component Schemas (component://{type}/{name})

    • Retrieves configuration schema for specific components
    • Supports listing all available schemas or getting a specific component's schema
    • Parameters:
      • type: Component type ("receiver", "processor", or "exporter")
      • name: Name of the specific component (optional)

Configuration

Usage with mcp clients

Add this to your mcp.json:

{
    "mcpServers": {
      "otelcol": {
        "url": "http://localhost:3001/sse"
      }
    }
}

Development

This is a local implementation of an MCP server for OpenTelemetry configuration. To use it:

  1. Clone the repository
  2. Build the project using the provided build scripts
  3. Configure your MCP client to use the local server implementation

License

This MCP server is licensed under the GPL-3.0 License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the GPL-3.0 License. For more details, please see the LICENSE file in the project repository.

otelcol-mcp FAQ

How does otelcol-mcp update OpenTelemetry component information?
It fetches the latest component metadata from GitHub and updates local resource files automatically.
Can otelcol-mcp manage all types of OpenTelemetry components?
Yes, it supports managing receivers, processors, and exporters dynamically.
Does otelcol-mcp require input parameters to update resources?
No, updating resources requires no input parameters and returns update statistics.
How can otelcol-mcp help in observability pipeline management?
It allows real-time configuration and management of OpenTelemetry Collectors components, streamlining observability workflows.
Is otelcol-mcp compatible with multiple LLM providers?
Yes, it can be integrated with models like OpenAI, Anthropic Claude, and Google Gemini for enhanced automation.
What metadata does otelcol-mcp provide for OpenTelemetry components?
It provides name, description, and stability information for receivers, processors, and exporters.
Can otelcol-mcp be used to automate configuration changes?
Yes, it supports dynamic configuration changes through MCP tools, enabling automation.
What is the benefit of using otelcol-mcp over manual configuration?
It reduces manual effort by automating component management and updates, improving accuracy and speed.