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    Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.
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    Apache 2.0
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    Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.
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    Apache 2.0
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    MCP server for the beacon log analytics platform, exposing beacon's REST API as MCP tools and resources for AI agents to query and analyse AI-assistant usage data.
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    MIT
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    An MCP server for the Uptrace observability platform that enables querying traces, spans, logs, and metrics through natural language. It provides tools for error analysis, service discovery, and trace visualization within MCP-compatible clients.
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    Model Context Protocol (MCP) Server for Vunet vuSmartMaps - A multi-tenant observability platform integration. Query metrics, traces, logs, and data models from your Vunet tenants using natural language through AI assistants like Claude, GitHub Copilot, or any MCP-compatible client.
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    MIT
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    Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.
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    MIT
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    An MCP server for the Wazuh SIEM/XDR platform that enables users to query agents, security alerts, detection rules, and decoders through Claude or other MCP clients. It provides specialized tools and prompts for investigating security alerts, performing agent health checks, and generating environmental security overviews.
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    MIT
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    A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.
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    MIT
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    A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.
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    MIT
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    Enables interaction with Datadog's monitoring and observability platform through the MCP protocol. Supports incident management, monitor status checks, log searches, metrics queries, APM traces, dashboard access, RUM analytics, host management, and downtime scheduling.
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    Apache 2.0
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    Enables interaction with Google Cloud Platform services through gcloud CLI, supporting operations like querying logs, checking Cloud Run status, managing secrets, executing Cloud SQL queries, and monitoring billing information.
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    MIT
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    Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.
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    MIT
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    Enables interaction with Sentry's error tracking platform to fetch and manage issue details, events, and project information through the Sentry API.
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    Enables interaction with Datadog's monitoring platform to search logs, search trace spans, and perform trace span aggregation for analysis.
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    MIT
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    A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.
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    Apache 2.0