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    Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.
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    MIT
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    A Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.
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    The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.
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    MIT
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    A Model Context Protocol server that provides AI agents with controlled read access to Datalust Seq instances for log analysis and monitoring. It enables agents to search events, execute data queries, and retrieve information about signals, dashboards, and alerts.
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    Connects AI coding assistants to Shipbook for investigating issues using real application logs with error classification, log search, and session tracing.
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    MIT
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    Self-hosted web analytics platform that exposes analytics data via the Model Context Protocol, enabling natural language queries about traffic, page views, web vitals, and custom events.
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    MIT
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    Patent-pending diagnostic + decisions-ledger engine for any host software system — operator briefs and a severity-gated MCP console.
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    Enables integration with Datadog APIs to monitor and retrieve information about monitors, metrics, dashboards, logs, events, and incidents through the Model Context Protocol.
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    MIT
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    Enables AI assistants to query and fetch error and performance monitoring data from AppSignal through the Model Context Protocol. Supports searching and retrieving detailed information about application errors and performance samples with flexible filtering options.
    Last updated
    5
    MIT