OpenTelemetry is an observability framework for cloud-native software. It provides tools, APIs, and SDKs to capture telemetry data from applications and process it for understanding their behavior and performance.
Uptime monitoring from your AI agent: create and diagnose checks (40 types: HTTP, TCP, DNS, SSL, ICMP, databases, message queues and more), read results and incidents, and manage status pages and maintenance windows. Built into the self-hostable SolidPing server, served over streamable HTTP at /api/v1/mcp.
42
12
AGPL 3.0
Why this server?
Enables access and analysis of OpenTelemetry traces and metrics data stored in Logfire, with tools for finding exceptions, retrieving trace information, and executing SQL queries against telemetry data.
A Model Context Protocol server that enables LLMs to retrieve and analyze OpenTelemetry traces and metrics from Logfire, supporting exception tracking and custom SQL queries against telemetry data.
4
18,894 PyPI
161
MIT
Why this server?
Accepts OTLP logs, metrics, and traces over JSON and protobuf, maps OTel service names and trace IDs into the bench, and can export bench events back to OTLP backends.
The logs of everything on one machine — app, build, GPU, containers, serial board, OS — interleaved in the order they happened, and readable by an agent. Read-only: it can tail, search and wait, and it cannot write, delete or configure anything.
2
9
6 npm
1
MIT
Why this server?
Allows exporting telemetry data via OpenTelemetry for observability.
Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
2
6
Apache 2.0
Why this server?
Core integration that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints, supporting all three OTLP wire formats (gRPC, HTTP/protobuf, HTTP/JSON) for comprehensive observability data collection.
An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.
11
MIT
Why this server?
Provides tools to access and search OpenTelemetry documentation, allowing users to fetch documentation pages in markdown format and search for specific content about tracing, metrics, instrumentation, and SDK configuration.
Enables access to OpenTelemetry documentation by fetching and converting pages to markdown format and searching content using Google Custom Search. Provides comprehensive documentation lookup and search capabilities for OpenTelemetry concepts, instrumentation, and configuration.
2
3
Apache 2.0
Why this server?
Enables distributed tracing via OpenTelemetry exporter.
Exposes Great Expectations data-quality checks as MCP tools for LLM agents, enabling data loading, expectation definition, validation, and result interpretation.
7
4
MIT
Why this server?
Correlate OpenTelemetry traces with static call graph for runtime correlation, identifying hot paths and dead code.
Instant codebase knowledge graph MCP server. It auto-detects languages, indexes functions, classes, and call chains, enabling LLMs to navigate code in milliseconds.
24
MIT
Why this server?
Provides tools for querying and analyzing OpenTelemetry traces, allowing AI agents to list recent traces, get span trees, search spans, and get service summaries.
