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Integrates Asana with Model Context Protocol (MCP) clients, such as Anthropic's Claude, enabling AI models to interact with and retrieve information from Asana.
Formats and serializes JSON-RPC responses for user interfaces within a larger application.
Executes predefined system commands with integrated safety checks and confirmation prompts.
Establishes a Model Context Protocol server to integrate AI tools with ServiceNow instances.
Provides cloud browser automation capabilities, enabling Large Language Models to interact with web pages and extract data.
Facilitates real-time currency conversion for large language models through the Model Context Protocol.
Manages and exposes AI 'skills' in a Claude-like style to other Large Language Models via a robust, extensible backend.
Aggregates multiple Model Context Protocol servers and exposes their combined tools through a unified HTTP API.
Access Tushare financial data and perform advanced quantitative analysis and backtesting through an MCP server.
Empower creators to develop intelligent applications with secure, user-friendly tools and frameworks.
Integrates Atlassian Jira and Confluence into Claude Code with secure API key authentication, offering comprehensive tools and workflow automation.
Performs comprehensive network analysis using tshark, offering 20 tools for capture, analysis, device identification, security auditing, and traffic profiling.
Manages MediaWiki wikis, enabling secure search, creation, editing, and management of pages, categories, and files.
Provides access to the Statbotics API for FIRST Robotics Competition statistical data and predictions, enabling AI assistants to retrieve FRC team ratings, event analytics, and match insights.
Enables AI assistants to browse, search, and discover MCP servers from the MCP Advisor registry.
Connects Telegram users with large language models through the Model Context Protocol.
Bridges AI assistants with Figma, enabling comprehensive interaction for design system extraction, creation, and debugging.
Automate comprehensive Android device interactions and management for AI agents.
Provides a robust memory layer for autonomous agents with provenance tracking, decay-weighted recall, and feedback-driven learning.
Create adaptive learning courses using AI agents, defining content as YAML knowledge graphs, and deploy with built-in diagnostics, spaced repetition, and billing.
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