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"Improving Cursor Efficiency and Smart Features" matching MCP servers:

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    A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.
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    Provides a universal read path for agents to extract facts, metadata, and provenance from local files and guarded remote URLs without using generative LLMs.
    MIT
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    Reads PDF, image, or video files by sniffing format and delegating to specialized sibling MCP servers, extracting facts and metadata without LLMs.
    179
    MIT
  • A
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    Smart Tree MCP cuts storage by up to 95% using quantum-context compression — not just files, but full project histories. Track, compress, and version smarter with zero-bloat ops across Git, FS, and memory.
    3,401
    266
    MIT
  • A
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    Provides LLM-optimized filesystem access with intelligent file pagination for large files, lightning-fast ripgrep-powered code search with regex support, and security sandboxing to safely explore and search codebases.
    7
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    1
    MIT
  • A
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    MCP server providing filesystem allowlist and pack-aware Qdrant RAG search. Enables reading files, listing directories, and performing filtered RAG searches with case and pack IDs.
    MIT
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    An MCP server that enables AI agents to create, read, edit, and manage Jupyter Notebook files programmatically, overcoming limitations in Cursor's native notebook support.
    161
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    A persistent SQLite-backed storage server that enables Cursor IDE's AI assistant to remember information across sessions with global or project-specific scopes. It supports complete CRUD operations, tag-based organization, and keyword search to manage user preferences and context effectively.
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    Combines KC Chat Panel session interaction with AgentDock computer control tools, enabling Cursor Cloud Agent to chat and operate the local machine via AgentDock.
    MIT
  • F
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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
    1
  • A
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    Enables Cursor's AI agent to perform supercharged local file search on Windows by connecting to Agent Ransack via MCP, supporting content and filename searches, regex, and deep folder scans.
    1
    MIT
  • A
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    TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
    2
    Apache 2.0