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    An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.
    6
    MIT
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    Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.
    18
    MIT
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    MCP server for the Chrome UX Report, providing real-user Core Web Vitals (LCP, INP, CLS) and historical trends for any origin or URL via natural language queries.
    3
    2
    MIT
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    Enables LLMs to analyze and manage DBOS workflows, including introspection, workflow management, and authentication, to help debug applications in development or production.
    25
    11
    MIT
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    A multi-tenant control plane for MCP that aggregates upstream MCP servers behind a single authenticated URL, with deny-by-default policy enforcement and a replayable audit trail.
    MIT
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    Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.
    9
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    Dead-man's-switch monitoring for cron jobs and AI agents: your job or agent pings a URL each run, and Kywio alerts you when the pings stop. MCP-native (create/ping/get heartbeat) plus REST — an outside observer for agents that can't detect their own death.
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    An MCP server proxy that reduces context window bloat by stripping metadata and fetching schemas on-demand, while managing backend MCP servers across multiple transports. It also provides a web dashboard for monitoring and restarting backend servers.
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    A Model Context Protocol server that provides comprehensive tools for monitoring and identifying performance bottlenecks in Logstash instances through an interactive web UI and JSON-RPC interface.
    1
  • F
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    A persistent activity log server that allows MCP-compatible AI assistants to log events, decisions, and system logs over HTTP, with a built-in web dashboard for monitoring and searching logs.
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    Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.
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    An MCP server for Grafana Loki that enables LLMs to query, tail, and analyze logs, featuring fuzzy container-name matching, compact output, and tools for log patterns, volume, and label discovery. It can run as a local stdio server or a containerized HTTP service.
    9
    MIT