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    Search 47,000+ marketing agencies and get AI-matched with fitted agencies, from Pick an Agency.
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    A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.
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    Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.
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    Accesses the doppelgangers.ai Social Media Context API to provide contextualized XML renderings of Twitter/X posts including conversation summaries and metadata. It enables semantic search and comprehensive post retrieval for high-quality analysis of social media trends and topics.
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    A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.
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    An MCP server that enables semantic search over local files or GitHub repositories by indexing content into a serverless vector database, allowing AI assistants to understand meaning rather than just keywords.
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    Local MCP server that provides semantic search (RAG) over code repositories, enabling AI clients like Claude and Gemini to access project context without manual re-upload.
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    Enables semantic search across documentation stored in Gemini FileSearchStores, returning AI-generated answers with source citations.
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    A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.
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    Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.
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    An MCP server and CLI tool that transforms codebases into AI-ready context through semantic search, call graph analysis, and incremental indexing. It enables AI assistants to perform hybrid vector and keyword searches to understand complex repository structures and cross-file relationships.
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    Enables AI-driven semantic code search by leveraging Windsurf's reverse-engineered protocol to perform multi-round local searches using natural language. It automatically executes bundled ripgrep and file operations to return relevant code snippets and file paths to MCP-compatible clients.
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    Enables efficient code navigation and retrieval through natural language search, BM25 ranking, and fuzzy matching across multiple programming languages. It drastically reduces token usage by allowing Claude to query specific code symbols and logic instead of reading entire files.
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    The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API. Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con
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    Enables AI agents to perform corpus analysis tasks such as discovery, search, and data access via the Model Context Protocol.
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    MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.
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    MIT