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Enables MCP-compatible assistants to generate images using the Together AI API.
Enables interaction with MinIO object storage through a Model-Context Protocol server and client.
Enables interaction with the Strava API through a Model Context Protocol (MCP) server.
Executes code in isolated Docker containers and returns the results to language models.
Enables data visualization within LLM workflows using Vega-Lite specifications.
Provides access to football statistics and live match data from the API-Football service.
Integrates with Zenodo records through the Model Context Protocol (MCP) for use in LLM workflows and IDEs.
Provides news information from various RSS feeds for integration with AI assistants.
Connects language models to the Royal Spanish Academy (RAE) API for enhanced Spanish language capabilities.
Provides standardized access to Bible data resources for Large Language Models using the Model Context Protocol.
Provides a unified Model Context Protocol (MCP) interface for multi-provider web search, maximizing available search capacity for automation and AI workflows.
Provides spatial context to Large Language Models by integrating geographic data services from the Géoplateforme.
Delivers precise, token-efficient code context to AI coding agents by leveraging hybrid semantic search and AST-aware analysis.
Provides mathematically scored financial context and sanitized data to AI agents, preventing hallucinations by focusing on daily closed market data.
Enables AI models to interact with TagoIO accounts, providing contextual access to devices, data, and platform resources.
Manages pharmaceutical structured product labels, providing secure access to FDA drug label data and an AI-powered chat interface.
Enhances Claude Code with fully automatic, per-project cognitive memory, leveraging local embeddings and hybrid search for improved development workflows.
Provides a next-generation AI memory system for agents, achieving state-of-the-art performance on long-term conversational memory benchmarks.
Provides coding agents with local, persistent memory, storing decisions, bugs, and context as Markdown for efficient retrieval.
Investigate ecosystem health by querying public environmental data from various sources using specified geographic coordinates.
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