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    A smart proxy server that prevents context window bloat by caching large tool responses to local files and returning compact resource links. It supports format conversion and data uploads, allowing LLMs to handle massive datasets without consuming excessive tokens.
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    SQL Server MCP server with AST-based query validation, read-only safety, schema exploration, ER diagram generation, and DBA toolkit integration (First Responder Kit, DarlingData, sp_WhoIsActive).
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    MIT
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    MCP Compass is a discovery and recommendation service that assists AI assistants in finding and understanding Model Context Protocol servers through natural language queries.
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    Enables AI assistants to access contextual knowledge from multiple repositories through Sequa's Contextual Knowledge Engine. Provides architecture-aware code understanding and cross-repository context for more accurate, production-ready code generation.
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    MIT
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    A Model Context Protocol server that enhances AI agents by providing deep semantic understanding of codebases, enabling more intelligent interactions through advanced code search and contextual awareness.
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    MIT
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    Connects MCP clients to databases like Snowflake, BigQuery, and Databricks through Alkemi's data platform, enabling natural language database queries with proper schema understanding and metadata management for consistent team-wide access.
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    MIT
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    Enables AI assistants to search and query Lucene/NRTSearch indexes using natural language, supporting full Lucene query syntax including Boolean, phrase, range, wildcard, and fuzzy searches with highlighting and custom field retrieval.
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    MIT
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    This advanced memory server facilitates neural memory-based sequence learning and prediction, enhancing code generation and understanding through state maintenance and manifold optimization as inspired by Google Research's framework.
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
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    MIT
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    Semantic code search for AI agents — hybrid vector + BM25 with cross-encoder reranking, AST-aware chunking for 14 languages, conversation memory, code annotations, and search analytics. Zero config, zero API keys. Just bunx
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    Apache 2.0
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    Self-hosted MCP server for indexing and searching code repositories via hybrid search and deep code understanding.
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    MIT