Starlark MCP, developed by Connyay, is a free MCP server tool built for the mcp platform. It uses the Starlark programming language for scripting and is implemented in Go, distributed as a Go module. This server connects AI-powered applications, acting as hosts for MCP clients, and integrates with various external tools and services. It provides a foundation for AI agents to interact with backend systems like data warehouses and APIs, enabling automation and data operations.

What does Starlark MCP connect to?

Starlark MCP functions as an MCP server, establishing connections with AI-powered applications that serve as MCP clients and hosts. It integrates with external tools and services, primarily for AI agents, allowing them to interact with various backend systems. This includes connecting to data warehouses for data retrieval and APIs for invoking specific functionalities. Compatible AI clients like Claude Desktop and Cursor can utilize its capabilities.

Core features and tools

The Starlark MCP server is designed to provide a configured environment with all necessary tools and resources registered for operation. It enables Starlark scripts, embedded within the server, to execute "host calls." These calls are essential for interacting with external systems, such as querying data warehouses or invoking APIs. While specific callable tools are not named, the server's architecture supports these core functionalities for AI agent interactions.

Who is it for?

Starlark MCP is intended for AI agents, developers, and engineers who need to automate tasks and manage workflows. It supports scenarios where AI agents require interaction with backend services for operations like moving money or deploying builds. Developers can use it to define and run workflows on Cadence without requiring worker redeployment. Skip this if your primary need is a simple API key authentication for production remote deployments.

How to get started

Access is granted through a standard OAuth authorization flow for remote HTTP deployments. For local stdio transport, authentication can involve environment-based credentials, such as API keys, or credentials provided by embedded third-party libraries.

Use cases

• Automating tasks and workflows for AI agents, including moving money, changing account state, approving refunds, or deploying builds.
• Defining and running workflows on Cadence without requiring worker redeployment.
• Generating reports and dashboards by querying data warehouses or invoking APIs.

Starlark MCP offers a powerful platform for connecting AI agents with backend services and automating complex workflows. Its Starlark scripting and Go implementation provide flexibility for various integration needs. It supports both local and remote deployments with appropriate authentication mechanisms.