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    Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.
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    Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.
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    AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.
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    Exposes UniFi Protect's Integration REST API as tools for Claude Code and other MCP clients, providing 73 tools to manage cameras, lights, sensors, and more with safety features like read-only mode and dry-run support.
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    A comprehensive MCP server providing OpenStack project management and monitoring capabilities with built-in safety controls and single-project scope.
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    MIT
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    MCP server implementation that enables LLMs to interact with Rollbar error tracking data, allowing users to list and analyze errors, view occurrences, track deployments, and access project information.
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    A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.
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    Enables AI assistants to interact with the aedifion cloud platform for building performance optimization and IoT data management. It provides over 95 tools for monitoring timeseries data, managing project components, and executing building analytics or controls.
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    MIT
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    A server that enables retrieval of Sentry issues through two simple tools - get a specific issue by URL/ID or get a list of issues from a project.
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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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    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
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    Provides access to WakaTime coding analytics data through MCP tools. Enables querying coding stats, activity summaries, project lists, and time tracking information from your WakaTime account.
    Last updated
    MIT