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"How to connect a backend project to MongoDB" matching MCP servers:

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    A comprehensive MCP toolkit for Java backend developers, providing 35 tools across 5 servers for database analysis, JVM diagnostics, migration assistance, Spring Boot monitoring, and Redis diagnostics.
    92
    MIT
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    Enables AI assistants to access App Store Connect data including financial metrics, subscription analytics, app performance data, and revenue insights. Provides real-time iOS app metrics through secure API integration with rate limiting and comprehensive reporting capabilities.
    14
    32
    MIT
  • F
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    Provides unified project context and monitoring capabilities including project health metrics, build diagnostics, Git integration, and infrastructure validation to initialize development sessions with comprehensive project information.
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    An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.
    6
    MIT
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    Connect AI assistants to Sentry for error tracking, issues, releases, events, and project management through the Model Context Protocol. Provides tools to list organizations, projects, issues, events, releases, teams, and members, as well as get details and update issue status.
    12
    42
    MIT
  • A
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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.
    6
    5
    MIT
  • A
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    quality
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    A production-grade MCP server for secure MongoDB CRUD operations with filtering, pagination, health monitoring, and rate limiting.
    41
    MIT
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    A Model Context Protocol server that provides secure database access to PostgreSQL through Kysely ORM, enabling natural language interaction with PostgreSQL databases. It offers 40+ MCP tools for querying, schema inspection, diagnostics, and Java backend monitoring.
    40
    131
    ISC
  • A
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    A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.
    8
    7
    MIT