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Integrates Xano databases with Smithery to enable Claude AI interactions with Xano data.
Enables LLMs to inspect MySQL database schemas and execute read-only queries.
Enables AI models to access and interact with real-time IoT data from the Acceleronix platform, enhancing AI applications with contextual device information.
Integrates with arXiv to search academic papers, extract detailed information, organize resources by topic, and generate AI-ready research prompts.
Enables AST-powered semantic code editing for language models by weaving code transformations at precise syntactic splice points, featuring automatic binary bundling of ast-grep.
Provides a simplified, functional Node.js implementation of an MCP server with advanced chat and consensus capabilities.
Provides a structured framework for creating, validating, and optimizing AI prompts using the RISEN methodology.
Provides a Python-based server to interact with Experimental Physics and Industrial Control System (EPICS) process variables, enabling retrieval, setting, and detailed information fetching of PVs.
Provides large language models with seamless Git repository interaction and automation capabilities through a Model Context Protocol server.
Orchestrates one-click development workflows for Claude Code, packaging AI capabilities as Skills within isolated sandbox environments.
Enables AI assistants to semantically search for quotes, verify attributions, and provide transparent source citations.
Provides AI-powered job recommendations, skill gap analysis, and a personalized career roadmap by parsing resumes and fetching real-time job listings.
Provides AI agents with programmatic access to the Epstein Exposed public API.
Equips AI agents with a specialized browser runtime that interprets web pages semantically and executes tasks intelligently, abstracting away low-level DOM operations.
Provides authenticated SQL query access to private geospatial datasets stored in S3 using DuckDB.
Manages shared versioned state for multi-agent AI workflows.
Provides a server that exposes RWIF-backed disk-native semantic memory, enabling models and agents to retrieve grounded semantic evidence without a heavyweight vector database.
Bridges LynxPrompt instances to an MCP server, empowering AI agents to manage configuration blueprints.
Provides persistent, zero-LLM, local-first memory with proactive recall for AI coding agents.
Generates fully-cited academic research papers with verified citations using specialized AI agents and vast academic sources.
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