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Integrates Jina's advanced AI APIs for web content extraction, search, and semantic processing into a remote Model Context Protocol (MCP) server.
Translates text and GitHub issue comments between languages using OpenAI models, configurable for various language pairs.
Delivers Stackpress-specific context to AI utilities for improved understanding and responses.
Implements a Model Context Protocol server, enabling AI models to integrate seamlessly with external systems and data sources.
Enhances red team operations by integrating artificial intelligence capabilities into the Sliver C2 framework.
Intelligently supervises and manages tasks for AI agents, providing LLM-powered insights and task breakdown.
Transforms documentation into intelligent, searchable knowledge bases using advanced vector embeddings and Retrieval-Augmented Generation.
Provides a simple Model Context Protocol (MCP) server implementation leveraging the Yupiik Fusion JSON-RPC API.
Provides a simple, experimental server for integrating tools with local AI chat agents.
Integrates local Llama models with Claude Desktop, enabling private, custom, and cost-effective AI operations through the Model Context Protocol.
Orchestrates multiple MCP services by positioning Llama Maverick as the central AI brain for intelligent management and request routing.
Analyzes forensic evidence to identify people and their connections, generating Python code for network visualization.
Integrates Jina AI's Reader, Embeddings, and Reranker APIs to offer a comprehensive suite of web content extraction, search, and AI-powered information processing tools.
Discovers and extracts comprehensive metadata from research papers, code repositories, and AI models using web scraping and API integration.
Analyzes project document context using artificial intelligence to answer queries and generate insights.
Connects AI models to the Pokémon world by providing extensive data and a battle simulation environment.
Enables AI assistants to interact with the MetaTrader 5 platform for trading and market data analysis.
Generates and serves dynamic bar and pie charts from structured data via a web-based API.
Enables AI models to interact with external tools and data sources.
Provides PyTorch AI/ML examples for Modal Context Protocol (MCP), Agent-to-Agent (A2A), RAG, and vLLM workflows, enabling reproducible and scalable pipelines for research and deployment.
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