"Comment perdre du poids (How to lose weight)" matching MCP servers:

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Postgres performance MCP server that analyzes hotspots, explains query plans, and detects dead-weight indexes. It aims to produce evidence-backed recommendations through a verification loop.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

Enterprise AI operator evaluation MCP server. 27 tools (22 read + 5 write) for measuring, benchmarking, diagnosing, and interv ening on how human operators use AI tools across 5 canonical metrics.

Provides secure access to the LogicMonitor API, enabling AI assistants to manage monitoring infrastructure through natural language commands.

Connects MCP clients to Gemini Cloud Assist APIs, enabling users to understand, manage, and troubleshoot their Google Cloud environment using natural language.

A read-only MCP server for the Auralogs logging platform, enabling AI agents to query production logs, search errors, and retrieve AI analyses without write access. It allows you to ask your coding assistant 'what's broken in production right now?' by connecting to your logs via a simple bearer auth key.

MCP server that wraps Drain3 for streaming log template mining, read-only matching, parameter extraction, and model persistence, exposing tools and resources to train on logs and query learned templates.

Provides access to Prometheus metrics and queries, allowing AI assistants to execute PromQL queries and analyze metrics data through standardized MCP interfaces.

Enables MCP-compatible applications to execute CrowdStrike NGSIEM security event searches with query validation and schema discovery.

Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.

Diagnoses Postgres job queues (pg-boss, graphile-worker) to identify retry storms, stuck jobs, missed schedules, and other issues, providing evidence-based recovery steps.

MCP server for Umami Analytics that provides read-only tools to query website stats, events, sessions, reports, and more, enabling natural language analytics queries.

Enables AI agents to interact with the Honeybadger error monitoring service to list, filter, and analyze fault data. It provides tools for fetching error lists and retrieving detailed fault information from Honeybadger projects.

An MCP server implementation that enables dynamic configuration of OpenTelemetry Collectors, allowing users to add, remove, and configure receivers, processors, and exporters through MCP tools.

Enables AI assistants to query Prometheus metrics, monitor alerts, and analyze system health through read-only access to your Prometheus server with built-in query safety and optional AI-powered metric analysis.

A read-only MCP server that enables agents to query and analyze Langfuse observability data, including traces, sessions, observations, scores, and metrics.

Enables AI assistants to retrieve and analyze Sentry issues, including error reports, stacktraces, and debugging information from Sentry.io.

Enables AI assistants to query Datadog metrics, logs, monitors, security signals, and billing data through natural language.

Enables AI agents to query and monitor service status, latency, and performance through configurable checks (HTTP, TCP, SSL, keyword, JSON-path) and exposes tools for listing services, retrieving metrics, and running on-demand checks.