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    DBeast MCP is a robust, security-first Model Context Protocol server designed to empower AI coding assistants (like Claude Desktop) with deep PostgreSQL database insights. Instead of just running basic SQL queries, DBeast equips your AI agent with tools to inspect active locks, audit slow queries, analyze table schemas, and safely generate index recommendations in real-time. Built specifically for
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    MIT
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    A Model Context Protocol server for the resQ emergency response system that integrates with digital twin simulations and coordination engines. It allows users to trigger simulations, generate deployment strategies, and monitor real-time drone status for incident response analysis.
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    Apache 2.0
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    Enables AI agents to audit Core Web Vitals, transform HTML for speed, generate PWAs, and export performance configurations via the Model Context Protocol.
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    MIT
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    Aggregates real-time threat intelligence from multiple sources including Feodo Tracker, URLhaus, CISA KEV, and ThreatFox, with IP/hash reputation checking via VirusTotal, AbuseIPDB, and Shodan for comprehensive security monitoring.
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    An MCP server that emits OpenTelemetry traces, metrics, and logs to OTLP endpoints in various formats. It includes tool-mimicry profiles to generate realistic traffic resembling common tools like nginx, postgres, and AWS Lambda for testing and demonstration purposes.
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    MIT
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    Read-only MCP server for Wealify KPI dashboard that allows AI agents to query KPI data, scoring status, alerts, member performance, and rubric documents via predefined tools and REST endpoints.
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    An MCP server that exposes Estuary Flow pipeline operations as typed tools, enabling agents to inspect pipeline health, publish captures and materializations, edit/restart tasks, and read landed documents via tool calls.
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    A dependency-free MCP server for Apache Incubator PMC oversight that helps identify podlings needing attention, assess graduation readiness, and generate podling briefings by combining lifecycle data and community health signals.
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    Enables inspection and querying of Firestore data and Cloud Function logs within the Firebase Emulator environment. It provides tools to navigate collections, retrieve documents, and filter function logs using regex and other criteria.
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    199 npm
    MIT
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    Exposes local Reqable network capture traffic to MCP clients for real-time monitoring and analysis of HTTP requests. It enables developers to query, search, and generate code from captured traffic stored locally within a private SQLite database.
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    36 PyPI
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    MIT
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    An MCP server that enables interaction with Elasticsearch and OpenSearch clusters for searching documents and managing indices. It provides tools for cluster health monitoring, index configuration, and general API requests.
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    Apache 2.0
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    Enables AI assistants to query and manage Zabbix monitoring data—hosts, items, triggers, problems, and health checks—and generate daily, weekly, and monthly operations reports.
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    GPL 3.0
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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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    An MCP server that integrates Google Search Console and Google Analytics 4 to provide unified SEO and web traffic analysis. It allows users to fetch search performance data, merge page metrics, and generate automated trend reports or actionable insights through tool calls.
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    An MCP server for searching and visualizing SolarWinds Observability logs, allowing users to query log data with filtering options and generate visual representations of log events over time.
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    2,763 npm
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    MIT
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    A Model Context Protocol server that enables AI tools to automatically log their activities with detailed metrics like timestamps, token usage, and costs into daily markdown worklog files.
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    Enables interaction with Gremlin's reliability management APIs to monitor service dependencies, run reliability experiments, generate reliability reports, and manage chaos engineering tests through natural language queries.
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    Apache 2.0
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    Enables AI coding agents to inspect active authenticated browser sessions and runtime state, capture user breadcrumbs and network/error telemetry, and generate Playwright/Cypress tests or MSW mock handlers through standard MCP tools.
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    A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports.
    MIT