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"Using MCP to streamline front-end and back-end data development with Cursor" matching MCP servers:

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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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    An enterprise-level MCP gateway and proxy that sits between an organization's MCP servers and clients. MCP Manager mitigates security threats, enables fine-grained permissions, enforces policies and guardrails, and generates comprehensive, end-to-end logs.
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    AGPL 3.0
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    Enables interaction with Sentry's error tracking and monitoring tools through a unified API, allowing natural language access to Sentry services.
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    MIT
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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.
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    MIT
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    An MCP server that provides AI assistants with direct access to application logs for on-demand searching, filtering, and analysis. It enables tools like Cursor to summarize log entries and identify errors within the development environment to streamline debugging.
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    MIT
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    MCP server for Kibana / Elasticsearch — log search, aggregations, index discovery, and dashboard browsing. Hits Elasticsearch REST API directly for log queries; falls back to Kibana Console proxy when no direct ES URL is configured. Supports ApiKey auth (best for agents), Basic auth, and anonymous access. All 5 tools are read-only (readOnlyHint: true). Returns structured JSON (outputSchema).
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    MIT
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    Provides read-only access to Jaeger distributed tracing data through the Model Context Protocol. Enables Claude and other MCP-capable agents to search traces, inspect spans, and analyze service dependencies directly within conversations.
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    MIT
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    Enables AI agents to interact with Freeplay, an ops platform for AI engineering teams, to analyze production logs, identify quality issues, iterate on prompts and agents using real data, and run experiments before deploying.
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    9
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    Apache 2.0