After using Cursor, Agentic AI has adopted a “you say, I do” model, which has become my primary way of using AI. This change has further inspired me to think: Is it possible to use Cursor or similar editors as a universal entry point for interacting with AI?
This idea is based on two main observations. First, when we use AI as a consultant, we often need to perform a lot of copy and paste operations, which are very natural within the Cursor editor. Just click the “Apply” button, and it will automatically insert AI’s answers into the document we are editing. Compared to traditional AI interfaces, this workflow aligns better with users’ work processes, especially during document creation, making Cursor a more suitable interface.
The second reason stems from the current shortcomings of the experience combining AI with search engines. Whether it’s ChatGPT’s “Search” feature or Proplexity and PoE’s Web Search Bot, their answers mostly skim through the first few search results and provide hasty conclusions. While this method works for single-turn Q&A, after using Agentic AI, we expect AI to provide higher-quality answers, such as by reviewing more results or iterating keywords multiple times to ultimately give a systematic summary. I am willing to wait longer for improved answer quality. This is precisely Cursor’s advantage when performing tasks as Agentic AI.
Therefore, I began a series of experiments to explore whether Cursor could serve as a universal entry point for AI usage, potentially replacing ChatGPT or Claude.AI. After some simple trials, I was very surprised by the results. Next, I will briefly introduce how to accomplish various common AI tasks through Cursor, especially traditional non-agent type AI applications, and compare their pros and cons.
Q&A
For the simplest general knowledge Q&A, users can directly input questions in the Cursor Chat window to obtain answers. This is not much different from traditional AI usage. A detail-oriented advantage is that users can directly call OpenAI, Anthropic, or even local private AIs for Q&A within the same interface.
In addition to this basic function, Cursor as an editor brings a significant convenience: it allows users to easily collect and save the results of Q&A, turning them into reusable documents.
Text Editing and Translation
Another amazing feature is that Cursor makes handling text-related tasks exceptionally convenient. For example, when I tried to translate a Chinese blog into English, I directly made a request in Cursor Chat, and the AI generated the English version of the article. After clicking “Apply”, Cursor automatically compared the Chinese and English documents, highlighting the differences. Even more interesting is that since the translated text maintains the same structure as the original, the comparison presents a graphical interface displaying the Chinese and English side by side, allowing users to intuitively modify the English content before accepting and copying the completed translation. Although this process was not the original intention of Cursor’s design, it is very convenient and natural.
Accessing Private Document RAG
Cursor provides precise search capabilities for large-scale code repositories, helping developers find relevant functions and assist in code writing. For non-development tasks, it can also serve as a RAG engine, combining private documents and information for high-quality Q&A.
For example, in the Q&A window, if a user sends a question using “Command + Enter”, Cursor will first conduct a round of searches within the current folder, displaying relevant documents and their relevance, and use this information to construct prompts for the final generation. This process is not limited to the Chat window but can also be executed through Cursor Composer as a step in Agentic AI operations.
In this way, Cursor can naturally integrate with private documents for Q&A and generate new insights. Compared to a purely conversational AI interface, Cursor’s ability to accumulate documents can further form a knowledge loop, facilitating subsequent queries and management. If you use knowledge management tools like Obsidian, Cursor will significantly enhance your knowledge retrieval and management efficiency.
Search
Another unexpected benefit is that Cursor can also be used as a powerful search engine. Although it does not have web search capabilities itself, through excellent extensibility, we can write small crawler tools for it to perform web scraping and searches, expanding its functionality.
For example, I once used Cursor to conduct a news search about OpenAI, which accurately summarized live broadcast content from the past 12 days and mentioned that OpenAI had released the official version of the O1 model. Compared to GPT’s search results, the content provided by Cursor is more detailed and accurate.
Personalization and Customization
In addition to the above features, Cursor can also achieve personalized and customized memory through prompts. For example, you can instruct Cursor to respond in Chinese, or specify certain websites for specific topics, or even customize its responses based on the document libraries you frequently use. This makes Cursor not just a tool that can grow, but also a personal assistant capable of learning and training.
Limitations
However, Cursor currently still has certain limitations. It does not have an open API and lacks a mobile version. Therefore, all operations must still be performed on desktop devices. For users who frequently interact with Agentic AI, mobile support is particularly important, as interaction can be done via voice or chat, allowing many tasks that originally required sitting at a computer to be moved to mobile devices.
Nevertheless, with the current technological advancements and continuous improvement of protocol standards, it is expected that these shortcomings will be addressed in the future, achieving more comprehensive support. I believe that with the development of mobile platforms and the popularization of Agentic AI, Cursor can play a greater role.