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"NFT documentation and guides" matching MCP servers:

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    Provides LLMs with up-to-date, version-specific documentation and code examples directly from library sources, eliminating outdated training data and hallucinated APIs by fetching current documentation at prompt time.
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    1,169,818
    MIT
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    Enables LLMs to scrape, index, and search modern and legacy Salesforce documentation by piercing complex Shadow DOM and iframe structures. It supports hierarchical spidering of entire guides and local RAG capabilities using a SQLite database for offline querying.
    5
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    MIT
  • F
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    Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.
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    Connects documentation, GA4 search analytics, Jenkins CI pipeline, and RAGAS-style evaluation to Claude for content gap analysis and documentation improvements.
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    Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.
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    MIT
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    Unified MCP server that orchestrates 5D Database and Documentation System plugins, providing AI agents with centralized tools for database queries, semantic search, documentation validation, and workflow coordination.
    59
    MIT
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    Provides real-time documentation retrieval for coding agents, answering implementation questions with compact, cited context assembled from developer documentation and live web search via a single MCP context tool.
    47
    MIT
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    A server that connects Claude to your documentation via Inkeep's API, enabling AI-powered interactions with your documentation content.
    24
    MIT
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    An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context
    21
    265
    MIT
  • A
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    Enables AI assistants to perform semantic, hybrid, and filtered search on indexed local documentation with RAG capabilities.
    2
    MIT
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    Aggregates documentation from multiple sources (llms.txt format or web scraping) and provides semantic search capabilities using vector embeddings and hybrid search for each documentation source.
    123
    MIT
  • A
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    Provides semantic search capabilities over the Plesk Extensions Guide documentation using Retrieval-Augmented Generation (RAG) and vector embeddings. It enables AI assistants to retrieve relevant technical information and answer natural language queries regarding Plesk extension development.