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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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    Enables LLM agents to query Dynatrace SaaS for observability data (logs, metrics, traces, entities, problems, vulnerabilities) and manage configurations (dashboards, notebooks, SLOs, synthetic monitors, settings).
    100
    MIT
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    Enables comprehensive management of Tailscale networks including device management, DNS configuration, file sharing via Taildrop, security monitoring, and network automation with built-in Grafana/Prometheus observability stack.
    4
    MIT
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    A Model Context Protocol server that analyzes various log types on Windows systems, allowing users to register, query, and analyze logs from different sources including Windows Event Logs, ETL files, and structured/unstructured text logs.
    5
    MIT
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    MCP server for tracing, logging, and debugging multi-agent systems by capturing sessions, spans, and events in a queryable trace tree.
    1
    MIT
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    Enables GPU profiling and performance analysis via NVIDIA Nsight Systems, allowing agents to profile binaries and aggregate statistics for kernels, memory copies, and NVTX ranges. It supports advanced analysis through interval tree construction and structural queries on profiling reports.
    5
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    Enables secure enterprise AI agents to access internal tools like GitHub, Gmail, Calendar, file systems, databases, and knowledge bases through the Model Context Protocol, with built-in security, audit, and observability.
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    An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.
    2
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    MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.
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    Apache 2.0
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    A Linux system monitoring MCP server that provides real-time information on CPU, memory, disk, network, processes, Docker, security, and more via MCP tools.
    28
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    MIT
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    Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.
    5
    167
    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