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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
    40
    1
    Apache 2.0
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    Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.
    MIT
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    Enables a local AI agent to investigate service incidents by querying read-only telemetry such as service health, metrics, logs, and traces, then produce verifiable assessments with evidence links and uncertainty.
    Apache 2.0
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    Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.
    MIT
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    A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.
    -
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    Enables AI agents and users to manage workspace files, monitor system metrics, take persistent notes, and retrieve weather data via MCP tools and resources.
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    An MCP server that connects to OPC UA-enabled industrial automation systems.
    31
    MIT
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    Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.
    MIT
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    Enables AI-powered debugging through structured logging with pattern recognition and intelligent analysis. Allows applications to write structured logs and receive actionable debugging insights based on error patterns and frequency analysis.
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    Enables users to query and analyze cloud spending, EC2 cost breakdowns, service-level spend, and model usage logs through natural-language interactions. It also supports cross-account spend retrieval when configured.
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    Enables querying AWS spend data via Cost Explorer and Amazon Bedrock usage data from CloudWatch logs using natural language. Supports cross-account access, local and remote deployment, and integration with Claude Desktop and LangGraph agents.
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    Enables MCP clients to inspect Google Play releases, reviews, Android vitals, and scoped bulk reports, and to prepare explicitly authorized changes using locally supplied service-account credentials. Reads are default, while optional writes and sensitive reads require explicit configuration and single-use execution.
    4
    13
    63 PyPI
    AGPL 3.0
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    An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.
    8
    3
    MIT
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    MCP server for system monitoring, enabling users to ask about CPU, memory, disk, network, and processes on their system.
    9
    3
    MIT
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    Bridges Microsoft Clarity's analytics API with Claude, enabling custom date ranges and page-level filtering on top of Clarity's native limitations.
    3
    11 npm
    MIT