3 مستودعات
Servers implementing the Model Context Protocol to expose Cloudflare edge services as tools for AI assistants.
Distinct from Cloudflare Workers Implementations: Distinct from Cloudflare Workers Implementations: focuses on the MCP protocol integration, not general serverless applications.
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Yao is an LLM agent framework and low-code web app builder designed for orchestrating autonomous AI agents. It provides a platform to design, deploy, and coordinate agents with specialized personas that can plan tasks, utilize external tools, and execute multi-stage pipelines. The project distinguishes itself through a Model Context Protocol server for connecting assistants to external binaries and HTTP services, and a gRPC remote execution engine that allows agents to manage remote servers and devices. It includes a model-agnostic provider bridge that supports dynamic switching between vario
Exposes tool servers running inside containers to agents via gRPC for extended capabilities.
This is a Model Context Protocol (MCP) server that exposes Cloudflare’s edge platform as a set of tools for AI assistants. It provides a unified interface for managing Cloudflare Workers, including deployment, versioning, and configuration, alongside access to Workers AI for running inference tasks using pre-trained models. The server also covers Cloudflare’s data storage services, including D1 serverless SQLite databases, KV globally distributed key-value stores, and R2 S3-compatible object storage. Beyond core resource management, the server enables automation and scheduling through cron tr
Implements the Model Context Protocol to expose Cloudflare edge services as tools for AI assistants.
This project is a Model Context Protocol server and AI agent database connector. It provides a standardized communication layer that allows language models to interact with relational data stores, read database schemas, and manage PostgreSQL database resources. The implementation acts as a serverless host for the Model Context Protocol, deploying on distributed edge functions to connect AI assistants to a project. This enables AI agents to perform database administration, execute SQL queries, and handle schema migrations through an AI-compatible interface. The system covers broader capabilit
Provides a serverless implementation of the Model Context Protocol to connect AI assistants to database resources via edge functions.