[ICML 2026] Meta Context Engineering via Agentic Skill Evolution

Model Context Protocol management suite/factory. An MCP that can generate and manage other local MCPs in multiple languages. Uses the official SDKs for code gen.

The official Rust SDK for the Model Context Protocol

The official Python SDK for Model Context Protocol servers and clients

The official Ruby SDK for the Model Context Protocol servers and clients.

The official TypeScript SDK for Model Context Protocol servers and clients

The official Go SDK for Model Context Protocol servers and clients. Maintained in collaboration with Google.

The official Java SDK for Model Context Protocol servers and clients. Maintained in collaboration with Spring AI

The official PHP SDK for Model Context Protocol servers and clients. Maintained in collaboration with The PHP Foundation.

The official C# SDK for Model Context Protocol servers and clients. Maintained in collaboration with Microsoft.

deep, reliable and confidential coding-context

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

Build effective agents using Model Context Protocol and simple workflow patterns

Absurdly easy Model Context Protocol Servers in Typescript

A type-safe solution to remote MCP communication, enabling effortless integration for centralized management of Model Context.

A Model Context Protocol (MCP) client library and debugging toolkit in Rust. This foundation provides both a production-ready SDK for building MCP integrations and the core architecture for an interactive debugger.

A generic, modular server for implementing the Model Context Protocol (MCP).

A type-safe implementation of the official Model Context Protocol (MCP) schema in Rust.

Modex is a Clojure MCP Library to augment your AI models with Tools, Resources & Prompts using Clojure (Model Context Protocol). Implements MCP Server & Client.

MCPSharp is a .NET library that helps you build Model Context Protocol (MCP) servers and clients - the standardized API protocol used by AI assistants and models.

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

Turn scattered knowledge, operational data, and history into source-linked context that your agents can inspect, explain, and reuse.

GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.

TypeScript-first framework for the Model Context Protocol (MCP). You write clean, typed code; FrontMCP handles the protocol, transport, DI, session/auth, and execution flow.