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"Understanding the term 'temporal' and its uses" matching MCP servers:

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    An MCP server for debugging Temporal workflows, enabling LLM-assisted inspection of workflow executions, detailed workflow info, and event history.
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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 natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.
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    MIT
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    A Model Context Protocol (MCP) server that lets an AI assistant read and operate the Lumics network monitoring platform via its REST API.
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    MIT
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    Enables AI agents to query Aptabase analytics through MCP, including metrics, top events, countries, sessions, and more. Uses the dashboard's cookie-authenticated endpoints, so it requires an Aptabase auth session cookie.
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    MIT
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    The MCP server provides an interface to the Datadog API, enabling seamless management of incidents, monitoring, logs, dashboards, metrics, traces, and hosts. Its extensible design allows easy integration of additional Datadog APIs for future expansions.
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    Apache 2.0
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    Enables AI assistants to manage and monitor Apache Kafka clusters through natural language, providing real-time operations, health monitoring, consumer lag analysis, and temporal trend detection for intelligent cluster management.
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    Provides observability for multi-agent workflows by tracking hierarchical task structure, architectural decisions, reasoning, encountered problems, code modifications with Git diffs, and temporal metrics.
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    Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.
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    MIT
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    A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.
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    MIT
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    RSigma is a Rust detection-engineering toolkit for the Sigma standard. Its MCP server (rsigma mcp serve) exposes the toolchain to AI agents over stdio or Streamable HTTP, with tools to author, lint, validate, and convert Sigma rules, evaluate and explain detections against log events, and inspect correlation state.
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    MIT
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    Streams live progress from long-running MCP tool calls to any connected client. Instrument a tool call with mcp-telemetry-sdk, and telemetry_subscribe pushes its steps, logs, cost, and completion over notifications/progress — no polling, and a job started in one session can be watched from a different one.
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    MIT
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    Session Watcher treats your prompt cache as inventory — it uses EOQ theory to tell you whether the current context is still worth carrying, and when to restart. Works with any session-based coding agent.
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    MIT
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    Privacy friendly, cookieless web analytics built MCP-first. "Add analytics to my Next.js app" → an AI agent runs the setup_analytics_for_site tool, picks the right install snippet, edits your layout file, and verifies the script is loading. OAuth onboarding, no API keys to paste.
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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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    MIT