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.
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.
Last updated
4
162
MIT
Why this server?
Provides performance monitoring and metrics collection through an OpenTelemetry-compatible system for tracking tool utilization and provider performance.
An MCP server that enables multi-provider AI collaboration using models like DeepSeek, OpenAI, and Anthropic through strategies such as parallel execution and consensus building. It provides specialized tools for side-by-side content comparison, quality review, and iterative refinement across different AI providers.
Last updated
4
1
MIT
Why this server?
Provides access to OpenTelemetry repositories, documentation, examples, semantic conventions, and instrumentation scoring to help implement high-quality observability.
Bridges AI coding assistants with the OpenTelemetry ecosystem, providing real-time access to repositories, documentation, examples, semantic conventions, and instrumentation scoring for high-quality observability.
Last updated
9
19
Apache 2.0
Why this server?
Provides distributed tracing capabilities through OpenTelemetry middleware, enabling observability and performance monitoring of MCP server operations.
Provides standards documentation and validation tools for the Darwin platform, including naming conventions and agent card validation. It enables AI agents to search platform standards and access resource templates for design and implementation.
Last updated
6
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.
Last updated
2
4
Apache 2.0
Why this server?
Integrate OpenTelemetry for observability, enabling monitoring of query performance and system health.
Self-hosted MCP server for live documentation, code audits, and best practices. 10 tools, unlimited library coverage (363+ curated + npm/PyPI/crates.io/Go fallback), no rate limits. Context7 alternative.
Last updated
14
606
3
Elastic 2.0
Why this server?
The instrumented agents emit OpenTelemetry-compatible traces, metrics, and logs for observability.
An MCP server that automatically instruments Python AI agents with the ioa-observe-sdk, adding OpenTelemetry-based tracing, metrics, and logs with zero manual effort.
