Search Results for "robust"

Telegram Drive is a powerful utility that enables you to organize your telegram files and much more. Teldrive stands out among similar tools, thanks to its implementation in Go, a language known for its efficiency. Its performance surpasses alternatives written in Python and other languages, with the exception of Rust. Teldrive not only excels in speed but also offers an intuitive user interface for efficient file interaction which other tool lacks. Its compatibility with Rclone further...

Foxy Contexts is a Golang library for building context servers that support the Model Context Protocol. It offers a declarative approach to defining tools, resources, and prompts, enabling developers to create robust context servers that enhance the capabilities of AI models. ​

A powerful and flexible Model Context Protocol (MCP) server implementation designed for seamless integration with Kubernetes and OpenShift environments, enabling enhanced interaction and management capabilities for AI assistants. ​

mcp-go is a Go implementation of the Model Context Protocol (MCP), designed to enable seamless integration between Large Language Model (LLM) applications and external data sources and tools. It abstracts the complexities of the protocol and server management, allowing developers to focus on building robust tools. The library is high-level and user-friendly, facilitating the development of MCP servers in Go. ​

...It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. Acontext also supports agent self-learning by distilling structured skills and experiences from previously completed tasks, which can later be reused or searched to improve future performance. It includes tools to interact with session data, background agents that monitor progress, and a dashboard that visualizes success rates, artifacts, and learned skills. ...

...The framework is built to be blockchain-agnostic, supporting multiple underlying ledger technologies so that applications can deploy across different networks with minimal rewrites. It also includes robust APIs for querying state, submitting transactions, and listening to events, helping bridge on-chain data with off-chain workflows.