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76,041 servers. Updated

"author:Mnehmos" matching MCP servers:

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    Enables searching and retrieving academic papers from arXiv by various criteria including title, author, and category, with support for extracting full text content from PDFs.
    4
    MIT
  • A
    license
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    quality
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    maintenance
    Detects schema mismatches between data producers and consumers through static analysis, supporting extraction, comparison, code generation, and automated validation with watch mode for MCP tools, APIs, and service contracts.
    11
    15
    MIT
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    Enables AI assistants to search and retrieve academic papers from arXiv through MCP tools, supporting search by various criteria, detailed paper information, category browsing, and PDF content extraction.
    4
    89
    2
  • F
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    Static analysis engine that detects schema mismatches between data producers (like MCP servers) and consumers (like client code), preventing runtime errors by validating contracts at development time.
    11
  • A
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    quality
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    Provides comprehensive computer control capabilities including shell commands, file operations, screen capture, keyboard/mouse input, window management, clipboard access, and system monitoring following the OODA loop pattern.
    12
    8
    MIT
  • A
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    quality
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    Provides persistent context synchronization and memory management for AI agents across sessions and projects, including file indexing, bug tracking, spatial navigation, and agent-to-agent handoff coordination.
    11
    3
    MIT
  • F
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    A backend server that executes advanced logic primitives and cognitive operations through the Model Context Protocol, allowing integration with various LLM providers for reasoning, data processing, and structured thought processing.
    29
  • F
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    Creates deterministic, auditable vector databases from any content source with deployable RAG applications. Supports multiple embedding providers and vector databases with fine-grained pipeline control or project-based workflows.
    11
    5
  • F
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    An MCP server that exposes FFmpeg as a structured tool set for AI agents, enabling timeline-based video editing, preview, rendering, and analysis with an optional LLM autopilot.