Enterprise AI Agents Spec defines a comprehensive specification for enterprise-grade AI agents, including manifest schemas for agent identity, description, triggers, memory management, and supported tools. The framework includes JSON-based tool definition formats, pipeline and workflow orchestration guidelines, and versioning standards to ensure consistent deployments. It supports extensibility through custom tool registration, security and governance best practices, and integration with various runtimes. By following its open standard, teams can build, share, and maintain AI agents across multiple environments, promoting collaboration, scalability, and uniform development processes within large organizations.

MCP Context Forge allows developers to define multiple channels such as text, code, embeddings, and custom metadata, orchestrating them into cohesive context windows for AI agents. Through its pipeline architecture, it automates segmentation of source data, enriches it with annotations, and merges channels based on configurable strategies like priority weighting or dynamic pruning. The framework supports adaptive context length management, retrieval-augmented generation, and seamless integration with IBM Watson and third-party LLMs, ensuring AI agents access relevant, concise, and up-to-date context. This improves performance in tasks like conversational AI, document Q&A, and automated summarization.