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    mistral-mcp is a TypeScript MCP server (spec 2025-11-25) that exposes the full Mistral AI API surface: 22 tools: chat, OCR, audio (Voxtral), vision, agents, embeddings, moderation, classification, files, batch, sampling, FIM (Codestral), streaming 2 resources: mistral://models, mistral://voices 6 curated prompts (French + English) with MCP argument completion Dual transport: stdio (default) + Str
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    An MCP server that enables AI assistants to perform web searches on Perplexity.ai using browser automation instead of an official API. It supports persistent authenticated sessions and returns search results along with cited sources directly to the client.
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    A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.
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    A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.
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    A CLI-based Model Context Protocol server that exposes PubNub SDK documentation and Functions resources to LLM-powered tools like Cursor IDE, enabling users to fetch documentation and interact with PubNub channels via natural language prompts.
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    Sleepycat
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    Official Bright Data server for the Model Context Protocol that enables AI assistants like Claude Desktop to reference and make decisions based on real-time public web data.
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    MIT
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    A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.
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    MIT
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    Enables AI assistants to search, list, and retrieve documentation from the Slice.js official GitHub repository. It provides full-text search capabilities and can deliver individual doc pages or a complete documentation bundle for comprehensive LLM context.
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    A production-ready MCP server that enables interaction with the AroFlo API to manage quotes, projects, and labor reporting. It features secure request signing and exposes API documentation as resources for enhanced context and tool surface.
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    A minimal TypeScript starter template for building Model Context Protocol (MCP) servers with auto-loading architecture for tools, resources, and prompts. Includes code generators, dual transport support (stdio/HTTP), and production-ready structure.
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    A Model Context Protocol server that enables AI assistants to interact with MongoDB Atlas resources through natural language, supporting database operations and Atlas management functions.
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    Apache 2.0
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    Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.
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    MIT