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Official LangChain MCP server for LangSmith providing conversation history, tracing, datasets, experiments, and billing usage access with comprehensive observability for AI applications.

Comprehensive Datadog Model Context Protocol server providing AI assistants with access to unified observability data including metrics, logs, APM traces, RUM, monitors, dashboards, and specialized toolsets for error tracking and feature flags.

Official Grafana Model Context Protocol server providing comprehensive observability tools for dashboards, Prometheus, Loki, Pyroscope datasource queries, alerting, incident management, and Sift investigations through AI assistants.

MCP server providing unified observability platform. Enterprise-backed by Datadog, supports VS Code, Cursor, Claude Code. Best for Datadog customers; production ready.

Connects AI to Sentry for fetching error contexts, stack traces, breadcrumbs, events, and performance data to enable accurate debugging suggestions.

Lightweight MCP gateway offering foundational security and observability including logging, guardrails against attacks and data exfiltration, plus EDR scanning to detect shadow MCP usage.

Model Context Protocol (MCP) Server for Langfuse Prompt Management. This server allows you to access and manage your Langfuse prompts through the Model Context Protocol.

The Logfire MCP Server by Pydantic provides integration with Logfire observability platform. Enables AI assistants to query logs, traces, and metrics from Pydantic Logfire through the Model Context Protocol.

Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo. Originally developed at Quickwit, it provides scalable full-text search capabilities.

Facilitates seamless integration with Alibaba Cloud's observability products, offering tools for efficient log and application monitoring.

Official MCP server connecting AI to Sentry error monitoring. Fetches full error context, stack traces, breadcrumbs, correlates with releases, searches issues, inspects performance data.

Observability and monitoring tool with its own MCP server for connecting to wider tools and services. Offers dynamic tool discovery for testing and evaluation to combat AI hallucinations.

Full-service API integration platform with extensive tools across categories, including MCP offerings for observability, authentication, and authorization. Serves as a one-stop shop for service provider integrations. Features simple connectivity requiring minimal code.

Managed MCP platform connecting AI agents to external APIs and services with observability, context management, and intelligent routing. Includes security, caching, and monitoring for production AI applications.

Puts performance and error data directly in the hands of your AI assistant for monitoring and observability.

Provide observability and tracing for debugging AI agents with AgentOps API. This MCP server enables developers to monitor, trace, and debug their AI agent applications through natural language interfaces.

An official Model Context Protocol server for Axiom, enabling AI assistants to query and analyze logs, traces, and events in Axiom's observability platform through natural language.

MCP server bringing real-time production context such as logs, metrics, and traces into local environments to auto-fix code faster using observability data.

MCP server for Last9 observability platform, enabling AI assistants to query and analyze telemetry data, logs, and monitoring information through the Model Context Protocol.

MCP server for querying and interacting with Kubernetes environments monitored by Metoro, providing AI agents with cluster observability and management capabilities.

An MCP server for Metoro, enabling AI assistants to query and interact with Metoro's Kubernetes observability and monitoring data through natural language.

MCP server for discovery, exploration, reporting, and root cause analysis using all observability data including metrics, logs, systems, containers, processes, and network connections.

Model Context Protocol server for New Relic observability platform integration, enabling AI assistants to query and analyze application performance monitoring data.

MCP implementation for Opik (by Comet ML) enabling seamless IDE integration and unified access to prompts, projects, traces, and metrics for LLM observability.

OpenTelemetry Collector MCP server that enables AI assistants to interact with OpenTelemetry data, providing observability data access through the Model Context Protocol.

Observability platform MCP server for Honeycomb, enabling AI agents to query telemetry data, analyze distributed traces, and debug production systems through natural language with OpenTelemetry integration.

Application performance monitoring integration providing real-time observability data access through AI assistants. Enables monitoring of problems, security concerns, metrics, and performance insights via natural language queries.

MCP Observability tooling from Grafana providing comprehensive monitoring for Model Context Protocol implementations. Enables visualization and analysis of MCP usage, performance metrics, and system health in Grafana Cloud.

A Model Context Protocol server for GreptimeDB, an open-source observability database handling metrics, logs, and traces in one engine. Enables AI assistants to query and analyze time-series data using SQL, TQL (PromQL-compatible), and RANGE queries with built-in security features.

An MCP server that connects to Airbrake error monitoring, enabling MCP-based automation and querying of collected application errors and aggregates.

An MCP server that integrates with Amazon CloudWatch Application Signals to provide application monitoring, tracing, and performance insights to MCP-enabled tools and agents.

An MCP server that enables metrics, alarms, and logs analysis for operational troubleshooting with Amazon CloudWatch, integrating observability capabilities into Model Context Protocol workflows.

An MCP Server for Better Stack observability and incident management, giving MCP clients access to monitoring, logging, and incident data through Model Context Protocol tools.

An MCP server for Cloudflare Observability at https://observability.mcp.cloudflare.com/sse, giving MCP tools programmatic access to Cloudflare observability and monitoring data via OAuth2.1.

MCP Server for Datadog, enabling model-context agents to query and interact with Datadog’s cloud monitoring and observability services.