Context.dev Integrations

Zapier is an AI-powered automation platform designed to help teams safely scale workflows, agents, and AI-driven processes. It connects over 8,000 apps into a single ecosystem, allowing businesses to automate work across tools without writing code. Zapier enables teams to build AI workflows, custom AI agents, and chatbots that handle real tasks automatically. The platform brings AI, data, and automation together in one place for faster execution. Zapier supports enterprise-grade security, compliance, and observability for mission-critical workflows. With pre-built templates and AI-assisted setup, teams can start automating in minutes. Trusted by leading global companies, Zapier turns AI from hype into measurable business results.

Make is a visual platform for anyone to design, build, and automate anything—from tasks and workflows to apps and systems—without coding. SMBs, startups, scaleups, teams, and enterprises around the world use Make to scale their business faster than ever. Make enables people to connect and create workflows at the speed of their ideas. With Make, anyone can build like a developer, launching solutions across all industries and business areas at a fraction of the cost and time. Make allows teams to visualize, modify, and collaborate on processes that scale as quickly as their organization. Whether you’re integrating sales and marketing tools, automating a customer journey, improving business operations, or building a custom back-end system—creating on Make is powerful, intuitive, and playful. As our Maker community has shown us, when the experience of building sparks as much joy as the solution, there are no limits to what's possible.

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

Wondering why Ruby is so popular? Its fans call it a beautiful, artful language. And yet, they say it’s handy and practical. Since its public release in 1995, Ruby has drawn devoted coders worldwide. In 2006, Ruby achieved mass acceptance. With active user groups formed in the world’s major cities and Ruby-related conferences filled to capacity. Ruby-Talk, the primary mailing list for discussion of the Ruby language, climbed to an average of 200 messages per day in 2006. It has dropped in recent years as the size of the community pushed discussion from one central list into many smaller groups. Ruby is ranked among the top 10 on most of the indices that measure the growth and popularity of programming languages worldwide (such as the TIOBE index). Much of the growth is attributed to the popularity of software written in Ruby, particularly the Ruby on Rails web framework.

TypeScript adds additional syntax to JavaScript to support a tighter integration with your editor. Catch errors early in your editor. TypeScript code converts to JavaScript, which runs anywhere JavaScript runs: In a browser, on Node.js or Deno and in your apps. TypeScript understands JavaScript and uses type inference to give you great tooling without additional code. TypeScript was used by 78% of the 2020 State of JS respondents, with 93% saying they would use it again. The most common kinds of errors that programmers write can be described as type errors: a certain kind of value was used where a different kind of value was expected. This could be due to simple typos, a failure to understand the API surface of a library, incorrect assumptions about runtime behavior, or other errors.

Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.