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    A Model Context Protocol server that integrates with Linear, enabling AI assistants to create, update, search, and comment on issues for project management and issue tracking.
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    Apache 2.0
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    MCP server for searching files on macOS by name or content using semantic and lexical search, providing file paths and line numbers for agents to read from.
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    MIT
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    Semantic search over any markdown corpus using local embeddings. Provides tools to search, reindex, and get index stats, with results including file paths, line numbers, and header breadcrumbs.
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    MIT
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    Enables LLMs to explore database schemas, execute read-only SQL queries, and perform data analysis on Apache Doris or MySQL-compatible databases through a standardized MCP interface with built-in analytical prompts.
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    MIT
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    A high-performance HTTP service that bridges Claude Code or other MCP clients with Linear's GraphQL API, enabling natural language interaction with Linear issues, comments, projects, and other entities without dealing with UUIDs.
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    2,581
    MIT
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    A command-line interface application that enables interactive chat with AI models through the Anthropic API, supporting document retrieval, command-based prompts, and extensible tool integrations.
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    Automatically synchronizes meeting transcripts from Otter.ai to a local SQLite database for easy browsing and management. It enables semantic and keyword-based search across meeting history through integrated MCP tools for Claude and Cursor.
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    Facilitates two-stage reasoning processes using DeepSeek for detailed analysis and supports multiple response models such as Claude 3.5 Sonnet and OpenRouter, maintaining conversation context and enhancing AI-driven interactions.
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    MIT
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    Integrates Dify's external knowledge base API with the Model Context Protocol to enable AI agents to retrieve and query relevant information. It supports relevance scoring, metadata filtering, and flexible configuration through environment variables or command-line arguments.
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    MIT
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    A Model Context Protocol server that combines DeepSeek R1's reasoning capabilities with Claude 3.5 Sonnet's response generation, enabling two-stage AI processing where DeepSeek's structured reasoning enhances Claude's final outputs.
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    MIT
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    Exposes LangChain and Anthropic Claude capabilities as tools for generating production-ready RAG systems, Supabase vector stores, and document ingestion pipelines. It enables users to instantly scaffold AI infrastructure and document processing code through natural language prompts in MCP-compatible clients.
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    Enables minimal interaction with Supabase databases through 4 essential tools for data querying, mutations, file storage, and user authentication. Designed for 70% less context usage than standard implementations with auto-truncated results and simplified parameters.
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