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    MCPWatch: observability for MCP servers. One line instruments any Python MCP server (FastMCP and the low-level Server) and tracks per-tool latency (p50/p95/p99), error rates, silent failures (empty/null returns and isError), and call volume. REST API, CLI, and alert hooks. MIT, no config required.
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    MIT
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    Enables AI assistants to search logs, query metrics, manage dashboards, analyze APM traces, and control monitors via Datadog APIs.
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    MIT
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    An evidence-first Prometheus MCP server that lets AI agents query production telemetry with detailed receipts including exact PromQL, timing, series count, and explicit warnings for empty, high-cardinality, or unreliable data.
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    MIT
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    An MCP server that enables AI assistants to query and analyze logs from Grafana Loki using LogQL, supporting label discovery and keyword search.
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    MCP server that transforms raw log query results into structured incident reports (Markdown, JSON, HTML) with correlation to git commits and tickets.
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    MIT
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    Lets agents query their own usage ledger captured by the Agentic Ledger proxy: sessions with full call traces, costs, loop runs, and stuck-loop flags. Tools include list_sessions, get_session, search, list_runs, get_run_status, and explain.
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    MIT
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    Enables searching Sumo Logic logs using the search_logs tool, with support for query parameters such as time range and maximum results.
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    MCP server for Beszel system monitoring that provides tools to list systems, containers, alerts, and query CPU, memory, disk, and network stats.
    Last updated
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    21
    MIT
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    Server for interacting with Honeycomb observability data. This server enables LLMs like Claude to directly analyze and query your Honeycomb datasets.
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    MIT
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    Enables interaction with Beszel system monitoring tool to query system and container statistics, manage alerts, and monitor infrastructure through its PocketBase backend.
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    6
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    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).
    Last updated
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    MIT
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    Enables AI agents to query PostHog analytics data directly via tool calls, including insights, events, feature flags, trends, and persons.
    Last updated
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    MIT
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    Enables LLMs to query and analyze logs from SEQ structured logging server with capabilities for searching events, retrieving event details, analyzing log patterns, and accessing saved searches.
    Last updated
    5
    MIT
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    Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.
    Last updated
    4
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    MIT