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"Managing and Working with Files" matching MCP servers:

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    An MCP server that packs repositories into AI-friendly files using the Repomix tool, supporting local and remote repositories with size estimation and compression. It enables users to efficiently feed entire codebases into AI models while managing context window limits.
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    Multi-Agent Mesh Network MCP server that spawns specialized AI agents working in parallel to solve complex coding problems, providing 3.64x faster performance through distributed intelligence.
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    MIT
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    A Model Context Protocol server for managing prompt templates as markdown files with YAML frontmatter, allowing users and LLMs to easily add, retrieve, and manage prompts.
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    MIT
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    A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.
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    Apache 2.0
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    Provides LLM access to Exasol database via MCP tools, including metadata reading and data queries, with an optional on-premise text-to-SQL (Governed SQL) translation.
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    MIT
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    Enables AI assistants to interact with Tencent Lexiang enterprise knowledge base for searching, reading, creating, and editing documents, managing files, and importing meeting recordings.
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    MIT
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    Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.
    MIT
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    A Model Context Protocol server integration that creates a persistent, searchable working memory for AI-assisted development by enabling automated context recall and knowledge persistence in Chroma, the open-source embedding database.
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    MIT
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    Enables LLMs to perform sophisticated web searches through proxy servers using Tavily's API, supporting comprehensive web searches, direct question answering, and recent news article retrieval with AI-extracted content.
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    MIT
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    Provides hybrid vector+BM25+reranker search and index-refresh tools over agent memory stored in markdown files, enabling forge agents to query memory across session, working, and docs tiers without direct file access.
    MIT
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    A Model Context Protocol server that exposes multiple AI tools over SSE transport with JWT-based secure authentication, allowing for dynamic tool registration and session management.
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    MIT
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    Enables you to chat with your PostgreSQL database via natural language, with GitHub OAuth authentication and role-based access control for secure read/write operations.
    MIT
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    A zero-ML-dependency keyword index MCP server for markdown context files, enabling fast search and retrieval of relevant files using RAKE and BM25, with a flat JSON index.
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    MIT
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    Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.
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    MIT