OpenTelemetry & Docker MCP Server (otel-server)

An intelligent Model Context Protocol (MCP) server that gives autonomous AI agents (like Claude) the ability to act as a Site Reliability Engineer (SRE).

This server bridges the gap between static code analysis and runtime observability. It allows LLMs to autonomously discover Docker containers, monitor resource utilization (OOM risks), tail logs, and drill down into OpenTelemetry distributed traces (via Jaeger), all safely and securely.

Key Features

Built specifically for how LLMs "think" and navigate:

• LLM Context Bounding: All tool outputs are wrapped in strict XML tags (e.g., <container_logs>, <trace_tree>) to prevent the LLM from hallucinating raw logs or trace data as prompt instructions.
• Built-in PII & Credential Redaction: Production logs and traces often contain sensitive data. This server automatically scrubs JWTs, Bearer tokens, emails, credit cards, and password fields before returning data to the LLM (e.g., replacing tokens with [REDACTED_BEARER]).
• Context Window Protection: Hard caps on log tails (max 500 lines) and trace trees (max 200 spans) prevent "wall of text" context window blowouts. Tools include grep_pattern and since/until parameters so the agent can scrub through time iteratively.
• Graceful Degradation: The server catches all API and socket exceptions, returning them as structured text (isError: true) rather than crashing the MCP process, allowing the agent to troubleshoot its own connection issues.

The Tools

This server registers 6 specialized tools with the MCP client:

Tool	Description
list_containers	Discovers local Docker containers by name or status. Essential for agents to map the environment without guessing Compose naming conventions.
get_container_status	Returns container state, health status, exit codes, and restart loops.
get_container_stats	Captures CPU, Memory, and I/O snapshots. Flags warnings when memory exceeds 90% to help diagnose OOMKilled containers that leave no crash logs.
fetch_logs	Tails container logs with ANSI stripping. Supports grep filtering and time-range navigation (since/until).
search_error_traces	Queries Jaeger for traces flagged with errors within a specific timeframe.
get_trace_tree	Recursively builds and formats a distributed trace into a highly readable, depth-first Markdown list showing span durations and error tags.

Installation & Setup

Prerequisites

• Node.js: v22 or higher
• Docker: Running locally (Docker Desktop, OrbStack, or Rancher Desktop)
• Jaeger: (Optional) Running locally or accessible via HTTP API

Build Instructions

# Clone the repository
git clone https://github.com/cruz-andr/otel-server.git
cd otel-server

# Install dependencies
npm install

# Build the TypeScript project
npm run build

Configuration

The server is configured via environment variables. Copy .env.example to .env or pass them directly through your MCP client.

Variable	Description	Default
DOCKER_SOCKET_PATH	Path to Docker socket	/var/run/docker.sock
JAEGER_BASE_URL	Jaeger HTTP API url	http://localhost:16686
JAEGER_TIMEOUT_MS	Timeout for Jaeger API requests (ms)	10000
MAX_LOG_LINES	Maximum number of log lines returned	500
DEFAULT_LOG_LINES	Default number of log lines when not specified	100
MAX_TRACE_SPANS	Maximum number of spans in a trace tree	200
DEFAULT_LOOKBACK	Default time window for trace searches	1h
REDACT_PATTERNS	Enable/disable PII scrubbing (set to "false" to disable)	true

Connecting to Claude Code

To use this server with Claude Code, run the following command in your terminal:

claude mcp add otel-server -- node /absolute/path/to/otel-server/build/index.js

(Optional) If you need to override the Docker socket p

... View full README on GitHub