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"The role of planning in project development" matching MCP servers:

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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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    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 secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.
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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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    Enables LLMs to answer Berserk observability questions by calling verified KQL tools instead of hand-authoring queries, with role-based tool filtering and automated query discovery.
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    MIT
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    A Model Context Protocol server that enables AI assistants to interact with Sentry for error tracking and monitoring, allowing retrieval and analysis of error data, project management, and performance monitoring through the Sentry API.
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    A Model Context Protocol (MCP) server that exposes 48 tools covering the full spectrum of iSuite enterprise administration — user management, role verification, job monitoring, scheduler control, batch execution, audit trail lookup, and configuration validation.
    48
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    Enables seamless interaction with the IBM Instana observability platform, allowing access to real-time observability data directly within development workflows.
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    Apache 2.0
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    This remote MCP server allows interaction with the Dynatrace observability platform. Bring real-time observability data directly into your development workflow.
    MIT
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    Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.
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    Real-time observability dashboard for monitoring AI agents in multi-agent development workflows, with live WebSocket updates of tool calls, sessions, and usage statistics.
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    Provides telemetry tools for retrieving recent logs and system metrics to support root-cause analysis of infrastructure incidents. Enables autonomous incident triage with grounded verification and human-in-the-loop remediation.