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"ICT Algorithmic Trading Strategy Development for TradingView" matching MCP servers:

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    Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.
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    Apache 2.0
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    A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.
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    MIT
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    Enables AI clients like Claude to triage, investigate, and operate Icinga installations through natural language, integrating with Icinga's REST APIs and providing deep awareness of monitoring plugins and historical performance data.
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    The Unlicense
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    Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.
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    Apache 2.0
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    A read-only MCP operations console for monitoring an algorithmic trading fleet, providing heartbeat, reconciliation, alert, and audit data through six typed tools.
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    MIT
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    MCP server for AI-assisted trading operations, enabling agents to diagnose and resolve FIX, OMS, and venue incidents through controlled tools and human approval.
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    MIT
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    A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.
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    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.
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    MIT
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    MCP server for Uptrack uptime monitoring. Manage monitors and incidents from AI agents like Claude, ChatGPT, and Cursor.
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    MIT
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    A remote MCP server that enables real-time interaction with the Dynatrace observability platform, bringing production-level monitoring data directly into development workflows.
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    MIT
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    Records runtime events from any app via zero-code instrumentation and exposes them to LLMs through MCP for autonomous debugging.
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    MIT
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    Enables AI assistants to query Cisco ThousandEyes v7 API for network monitoring data including tests, agents, alerts, dashboards, and test results (network, page-load, web-transactions, path visualization) for faster troubleshooting through natural language.
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    Apache 2.0