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"Assistance with Java development" 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.
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    MIT
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    A JVM monitoring and control platform server based on Arthas that provides a Python interface for monitoring and analyzing Java processes with capabilities for thread analysis, memory monitoring, and performance diagnostics.
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    MIT
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    Query Langfuse traces, schema and datasets, scores and metrics, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.
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    MIT
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    A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.
    167
    Apache 2.0
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    Enables real-time data streaming through Server-Sent Events with timestamp broadcasting and server monitoring capabilities. Optimized for deployment on Render.com with health checks and status endpoints.
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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.
    ISC
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    AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.
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    MIT
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    MCP server for profiling Java applications via JDK utilities (jcmd, jfr, jps). Enables AI assistants to diagnose performance, analyze threads, and inspect JFR recordings without manual CLI usage.
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    MIT
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    Enables tracking and analyzing development time through the Wakapi API. Provides tools to retrieve coding statistics, project details, leaderboards, and recent activity logs for productivity insights.
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    Apache 2.0
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    A Model Context Protocol server that connects AI agents to live Java processes via Alibaba Arthas, enabling real-time diagnostics, debugging, and performance analysis without code changes.
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    MIT
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    Enables monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.
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    Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.
    8