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"How to write and execute queries in InfluxDB" matching MCP servers:

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    Enables interaction with InfluxDB v3 (Core/Enterprise/Cloud Dedicated) through MCP clients. Supports database management, data querying and writing, schema inspection, and token administration operations.
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    MIT
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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.
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    Apache 2.0
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    Enables users to generate and execute InfluxDB queries using natural language commands in Korean. Supports querying metrics like CPU usage, memory status, and system monitoring data through conversational interface.
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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.
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    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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    An MCP server that enables querying logs and metrics from Graylog, Prometheus, and InfluxDB 2.x. It provides tools for executing Lucene log searches, PromQL queries, and Flux queries directly within MCP-compatible clients.
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    MIT
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    MCP server for InfluxDB 2.x, tuned for Home Assistant long-term storage, enabling reading sensor history, finding anomalies, and running Flux queries.
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    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.
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    MIT
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    Enables AI assistants to execute PromQL queries and discover metrics within AWS Managed Prometheus (AMP) using SigV4 authentication. It provides tools for instant and range queries, label management, and metric discovery in secure, VPC-isolated environments.
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    Tamper-evident audit logging for AI decisions. Three tools (record_decision, verify_decision, list_decisions) write to a regulator-grade ledger built on AWS S3 Object Lock with 7-year retention. Designed for EU AI Act Article 12 and FCA SS1/23 evidence requirements. Try zero-config: npx audit-ledger-mcp boots in sandbox mode against a public hosted tenant.
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    Apache 2.0
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    DBeast MCP is a robust, security-first Model Context Protocol server designed to empower AI coding assistants (like Claude Desktop) with deep PostgreSQL database insights. Instead of just running basic SQL queries, DBeast equips your AI agent with tools to inspect active locks, audit slow queries, analyze table schemas, and safely generate index recommendations in real-time. Built specifically for
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    MIT
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    Enables AI agents to read and optionally write to PostgreSQL databases through a multi-project setup with schema inspection, query execution, and performance analysis tools.
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    Exposes a Kubernetes cluster to MCP-compatible AI clients, enabling read-only and optional write operations on cluster resources like pods, deployments, and namespaces through natural language.
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    MIT
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    Enables management of endpoint inventory, patching, and vulnerabilities through the Action1 REST API, with read-only access by default and optional write support for update approvals.
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    15
    Apache 2.0