AI-Powered OpenTelemetry Analysis

by shiftyp

12 stars

336 downloads

Not rated

GitHub

Developer Tools

Description

# AI-Powered OpenTelemetry Analysis ## 🚀 Transform Your Observability Data into Actionable Intelligence **Stop drowning in dashboards. Start having conversations with your telemetry data.** Modern applications generate massive amounts of observability data through OpenTelemetry…

About

Details

Author: shiftyp
GitHub stars: 12
Downloads: 336
Categories: Developer Tools

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name AI-Powered OpenTelemetry Analysis

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

From the repository

Add the server to your MCP settings for Windsurf/Claude Desktop using environment variables like OPENSEARCH_URL, USERNAME, PASSWORD, and optionally OPENAI_API_KEY. For developers, clone the repo, install dependencies, configure .env, build, and integrate with your MCP client via a direct node command to dist/server.js.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "ai-powered opentelemetry analysis": {
            "otel-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "otel-mcp-server"
                ],
                "env": {
                    "OPENSEARCH_URL": "http://localhost:9200",
                    "USERNAME": "elastic",
                    "PASSWORD": "changeme",
                    "OPENAI_API_KEY": "sk-..."
                }
            }
        }
    }
}

McpServers

{
    "otel-mcp-server": {
        "command": "npx",
        "args": [
            "-y",
            "otel-mcp-server"
        ],
        "env": {
            "OPENSEARCH_URL": "http://localhost:9200",
            "USERNAME": "elastic",
            "PASSWORD": "changeme",
            "OPENAI_API_KEY": "sk-..."
        }
    }
}

AI-Powered OpenTelemetry Analysis

🚀 Transform Your Observability Data into Actionable Intelligence

Stop drowning in dashboards. Start having conversations with your telemetry data.

Modern applications generate massive amounts of observability data through OpenTelemetry - traces, metrics, and logs that contain the answers to every operational question. But finding those answers requires navigating complex query languages, building custom dashboards, and manually correlating signals across different data types.

What if you could just ask?

This MCP server bridges the gap between AI assistants and your OpenTelemetry data, enabling natural language interactions with your entire observability stack:

- "Show me all errors in the payment service from the last hour" - The AI queries your traces and logs, finding patterns you might have missed
- "Why is the checkout service slow?" - Get instant analysis of latency patterns, bottlenecks, and anomalies
- "What changed in my system between 2pm and 3pm yesterday?" - Compare metrics, identify anomalies, and correlate events across services
- "Find the root cause of the authentication failures" - Let AI trace error propagation through your distributed system

📡 What is OpenTelemetry?

OpenTelemetry (OTEL) is the industry-standard framework for collecting and managing telemetry data from your applications. It provides a vendor-neutral way to instrument, generate, collect, and export telemetry data.

The Three Pillars of Observability

OpenTelemetry captures three essential types of telemetry data:

Traces
- Track requests as they flow through distributed systems
- Show the complete journey of a transaction across multiple services
- Include timing, status, and contextual information for each step
- Example: Following a user's checkout process from frontend → cart service → payment service → notification service

Metrics
- Numerical measurements of system behavior over time
- Include counters, gauges, and histograms
- Track resource usage, business KPIs, and performance indicators
- Example: CPU usage, request latency percentiles, items sold per minute

Logs
- Structured records of discrete events
- Include timestamps, severity levels, and contextual attributes
- Can be correlated with traces and metrics for full context
- Example: Error messages, audit trails, debugging information

Why OpenTelemetry Matters

Traditional monitoring tools often lock you into proprietary formats. OpenTelemetry breaks these silos by:

1. Vendor Neutrality: Collect once, send anywhere - works with Elasticsearch, OpenSearch, Jaeger, Prometheus, and more
2. Unified Collection: Single instrumentation for all telemetry types
3. Automatic Context: Built-in correlation between traces, metrics, and logs
4. Industry Standard: Backed by the Cloud Native Computing Foundation

How This Server Enhances OpenTelemetry

While OpenTelemetry solves data collection, analyzing that data still requires expertise. This MCP server makes your OpenTelemetry data conversational:

- No Query Language Required: Ask questions in plain English instead of writing complex queries
- Cross-Signal Correlation: AI automatically correlates traces, metrics, and logs
- Pattern Recognition: Discover anomalies and trends you might miss manually
- Contextual Understanding: AI understands service relationships and dependencies

Learn more:
- OpenTelemetry Documentation
- OTEL Collector Configuration
- Instrumenting Your Application
- OpenTelemetry Demo Application

💡 Why This Matters

Traditional observability tools excel at collecting and storing data, but they still require human expertise to extract insights. By connecting AI directly to your telemetry data, you get:

Instant Incident Response

When an outage hits at 3am, you don't have time to craft complex queries. Ask the AI to investigate error patterns, trace failures through your system, and identify the root cause - all in natural language.

Proactive Problem Detection

Instead of setting up hundreds of static alerts, let AI continuously analyze your data for anomalies. Ask questions like "Are there any unusual patterns in today's traffic?" and get intelligent analysis based on historical baselines.

Democratized Observability

Not everyone on your team is a query expert. With natural language access, developers, SREs, and even product managers can explore system behavior without learning complex query languages.

Context-Aware Development

While reviewing code or designing features, developers can instantly check how similar code performs in production, what errors it generates, and how it impacts system performance.

🎯 Real-World Use Cases

During Incidents

- "Find all traces with errors in the authentication flow" - "Show me service dependency failures in the last 30 minutes" - "Which services are experiencing elevated latency?"

Performance Analysis

- "Identify the slowest operations in the checkout service" - "Compare today's CPU usage with last week's baseline" - "Find memory leaks in the cart service"

System Understanding

- "Map out all service dependencies" - "Show me the critical path for order processing" - "Which services communicate with the payment gateway?"

Anomaly Detection

- "Find unusual log patterns in the last hour" - "Detect metric anomalies across all services" - "Show me rare error messages that started appearing today"

🛠️ How It Works

This server implements the Model Context Protocol (MCP), providing AI assistants with a structured interface to your OpenTelemetry data stored in Elasticsearch/OpenSearch. When you ask a question, the AI:

1. Understands your intent and identifies relevant data types (traces, metrics, or logs)
2. Constructs appropriate queries using the provided tools
3. Analyzes the results and presents insights in natural language
4. Can perform follow-up queries to dive deeper into issues

⚡ Quick Start

For Windsurf/Claude Desktop Users

Add this to your MCP settings:

{
  "mcpServers": {
    "otel-mcp-server": {
      "command": "npx",
      "args": ["-y", "otel-mcp-server"],
      "env": {
        "OPENSEARCH_URL": "http://localhost:9200",
        "USERNAME": "elastic",
        "PASSWORD": "changeme",
        "OPENAI_API_KEY": "sk-..."  // Optional: for ML-powered features
      }
    }
  }
}

Note: You can use either ELASTICSEARCH_URL or OPENSEARCH_URL - both work.

For Developers

```bash

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

AI-Powered OpenTelemetry Analysis

🚀 Transform Your Observability Data into Actionable Intelligence

📡 What is OpenTelemetry?

The Three Pillars of Observability

Why OpenTelemetry Matters

How This Server Enhances OpenTelemetry

💡 Why This Matters

Instant Incident Response

Proactive Problem Detection

Democratized Observability

Context-Aware Development

🎯 Real-World Use Cases

During Incidents

Performance Analysis

System Understanding

Anomaly Detection

🛠️ How It Works

⚡ Quick Start

For Windsurf/Claude Desktop Users

For Developers

Install

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