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Analyzes Twitter data to provide real-time financial market sentiment and trend analysis.
Enables AI clients to perform advanced Google Custom Searches, extract web content, and conduct specialized research.
Provides a comprehensive set of tools for interacting with the Treasure Data API within AI development environments.
Facilitates SQL querying of Excel files via Claude AI, automatically generating and executing queries without requiring SQL expertise.
Retrieves comprehensive system information and diagnostics for CPU, memory, disk, network, processes, battery, and hardware.
Provides an MCP server to programmatically manage Google Tag Manager accounts, containers, and resources.
Inspects macOS processes, network connections, and code signing status to identify and flag suspicious activity with severity-ranked explanations.
Enables AI agents to share verified memories in real-time through a high-performance, decentralized P2P infrastructure.
Connects AI assistants to real-time banking regulatory data from over 100 sources.
Provides comprehensive real-time market data, technical analysis, options analytics, and portfolio management for the Indian stock market.
Analyzes local Docker logs from multi-container development setups using natural language via VSCode Copilot Agent Mode.
Transforms a local LLM into an agentic financial research assistant for Indian NSE stocks, leveraging the Model Context Protocol.
Provides AI assistants with live access to comprehensive workforce competitive intelligence, including hiring signals, patent inventor movement, technical capability maps, and executive flight risk for any company.
Automate academic research technology scouting, university tech transfer intelligence, and lab profiling by connecting to 8 live academic databases for AI agent-driven analysis.
Assesses DORA compliance in real-time for financial entities, utilizing 22 specialized tools for traffic-light scoring of DORA articles.
Facilitates interaction between MCP clients and Siemens PLCs by acting as a server for python-snap7.
Provides a dedicated complaint box for AI agents to log bugs, report issues, and suggest improvements.
Automates B2B lead scoring with engagement tracking and prioritization for sales and marketing efforts.
Provides AI agents with real-time access to a vast array of structured data sources and specialized tools through a single Model Context Protocol connection.
Provides an observational signal surface for dispute and chargeback data in agent-to-agent commerce.
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