In the era of rapid AI technological advancement, agent applications are gradually penetrating various industries. However, high development thresholds, complex technical architectures, and scattered tool resources have deterred many developers and enterprises. Xingchen Agent, an AI agent development platform launched by iFlytek, breaks down the technical barriers to agent development with its core advantages of “fully open architecture, low-threshold development, and full-scenario adaptation”. It provides a one-stop agent development solution for individuals ranging from zero-based enthusiasts to professional developers, making “everyone can develop agents” a reality.
The most prominent advantage of Xingchen Agent lies in its fully open model and tool architecture. By being compatible with multi-source resources and integrating rich plug-ins, it constructs a flexible and powerful development ecosystem, fundamentally solving the pain points of “scattered resources and difficult adaptation”.
The platform supports the instant use of multi-source high-quality models, covering a full-stack model capability matrix including complex reasoning, multi-modal generation, and intelligent decision-making. Whether it is a financial analysis scenario that requires high-precision text processing or an educational application scenario that relies on image and voice interaction, developers can flexibly select and combine models according to business needs. For example, when developing an “AI programming tutoring agent”, a model proficient in code logic reasoning can be used to answer programming questions, and a multi-modal model can be matched to realize visual code explanation. If it is necessary to enhance the natural language interaction capability of the agent later, a more suitable language model can be directly integrated without reconstructing the overall architecture, which greatly reduces the cost of model iteration.
Xingchen Agent has launched more than 16,000 high-quality
MCP Servers (Modular Capability Plug-ins), covering various scenarios such as AI capabilities, life services, academic research, and entertainment, and the number is continuously expanding. These plug-ins are like “ready-made parts”, so developers do not need to develop basic functions from scratch. If you want to develop a travel planning agent, you can directly call MCP Servers such as “weather query”, “high-speed rail ticket booking”, and “scenic spot recommendation”. When developing an office assistant, you can quickly integrate plug-ins such as “document translation”, “PPT generation”, and “schedule management”. At the same time, the platform provides rich industry templates. For example, with the “AI podcast generation” template, developers only need to modify parameters such as the radio name, style, and host voice to quickly generate podcast programs, realizing “second-level reuse” and significantly shortening the development cycle.
Xingchen Agent innovatively builds a progressive development system of “zero-code – low-code – fully independent development”. No matter whether developers have programming foundations or not, they can find a development method suitable for themselves, truly lowering the threshold of agent development.
For zero-based developers, the platform supports quick creation of agents through “Prompt configuration”. You only need to enter a demand description in the interface, such as “develop a small assistant that can generate operation copy based on the keywords input by users”, select an adapted model and required plug-ins (such as “copy style optimization” and “keyword extraction”), and the agent can be quickly generated and put into use without writing a single line of code. At the same time, the platform provides the “drag-and-drop connection design” function. By dragging and dropping modules such as “Agent intelligent decision-making” and “tool call” and connecting them in series, you can complete the arrangement of simple task processes and quickly implement your ideas.
For users with certain development foundations, the low-code development mode provides higher flexibility. Developers can customize node logic in the “canvas interface”. For example, add a “user preference analysis” node to the “travel planning assistant” and implement a more accurate destination recommendation algorithm through code snippets. They can also flexibly configure permissions and set the agent as “private use” (such as an internal enterprise management tool) or “shared release” (such as a service-oriented agent for the public). The platform also supports one-click release of lightweight workflows as MCP Servers, further expanding the boundary of tool capabilities to meet personalized development needs.
For professional developers, Xingchen Agent provides full independent development support, allowing in-depth customization of the core logic and functions of the agent. Developers can use the “model fine-tuning” function of the platform to optimize the model effect based on specific industry data. For example, import historical investment data into the financial field agent to improve the accuracy of investment suggestions. Through the “full-link evaluation tool”, batch use case management and manual evaluation can be carried out to verify the performance of the agent in different scenarios and ensure its stability and reliability. In addition, the platform will launch functions such as a multi-agent collaboration framework and long-short-term memory in the future, providing stronger technical support for complex agent development.
In addition to the open architecture and low-threshold development mode, Xingchen Agent also has a series of practical functions, which comprehensively improve the efficiency of developers and the application value of agents from development optimization to release and operation.
Different models often have differences in response effects to the same Prompt. The platform supports the multi-model Prompt comparison and optimization function. Developers can input Prompts and select multiple models for testing at the same time, intuitively compare the output results, and find the most suitable model and Prompt combination for the scenario. For example, when developing an “English reading assistant”, by comparing the responses of different models to the “long and difficult sentence analysis” Prompt, select the model with the clearest and most understandable analysis to ensure the use effect of the agent in the educational scenario.
To ensure the stability and practicality of the agent, the platform provides a full-link evaluation tool, supporting batch use case management and manual evaluation. Developers can upload test data (such as common user questions and business scenario cases) to comprehensively test indicators such as the response speed and accuracy of the agent. If it is found that the agent performs poorly in a certain type of problem during the test, it can be optimized through methods such as “model fine-tuning” and “plug-in upgrade” to form a closed loop of “development – testing – optimization”. At the same time, the platform will continue to launch office efficiency plug-ins and scenario-based RAG solutions to help the agent continuously iterate and upgrade.
After the development is completed, developers can release the agent as an Http application or API service, and easily integrate it with existing business systems. For example, integrate the “customer service agent” into the official enterprise website or WeChat official account to realize 24-hour automatic response. It can also be released to the “Agent Plaza” for other users to use or learn from, forming a benign developer ecosystem. The platform also supports team collaboration functions, allowing multiple people to participate in the development, testing, and operation and maintenance of the agent, improving team development efficiency.
With its strong development capabilities and rich resources, the application scenarios of Xingchen Agent have penetrated into various industries, bringing intelligent changes to different fields.
In the field of life services, Xingchen Agent can develop various practical assistants. For example, the “travel planning assistant” can call MCP Servers such as weather query, scenic spot query, and high-speed rail ticket query, and combine the user’s travel time, budget, and interest preferences (such as parent-child travel and outdoor hiking) to generate a personalized plan including itinerary arrangement, transportation booking, and scenic spot strategies. The “daily health butler” agent can access plug-ins such as physical examination data query, diet advice, and exercise plan generation to provide users with customized health management services.
Workplace professionals can use Xingchen Agent to develop “office efficiency tools”. For example, the “code engineer assistant” can automatically generate code snippets and troubleshoot simple bugs. The “operation copy assistant” can quickly generate promotion copy for platforms such as Moments and Xiaohongshu according to product selling points and target groups. Creators can use the “novel creation master” agent to obtain plot development suggestions and chapter content by inputting story outlines and character settings. They can also use the “AI podcast generation” template to quickly produce audio programs that conform to their personal styles.
In vertical industries, Xingchen Agent can also play an important role. In the financial field, agents developed in cooperation with financial institutions can integrate market data and user risk preferences to provide personalized investment advice and improve the customer service experience. In the education field, the “programming tutoring agent” can answer students’ programming questions and provide practice question banks, reducing the teaching burden of teachers. In the enterprise service field, the “project management agent” can access plug-ins such as task assignment, progress tracking, and data analysis to optimize the team collaboration process and improve operation efficiency.
The development process of Xingchen Agent is simple and clear, even beginners can quickly master it:
- Registration and Login: Visit the official website of iFlytek Xingchen Agent, complete account registration and login;
- Create an Agent: Click “New Agent”, fill in the name and select “Custom Creation” to enter the canvas interface;
- Configure Nodes and Plug-Ins: Add an “Agent Intelligent Decision-Making” node, select an adapted model, call the required MCP Server (such as Amap and document processing plug-ins), and configure information such as role settings;
- Testing and Optimization: Upload test data through the platform’s evaluation tool to verify the effect of the agent. If optimization is needed, perform model fine-tuning or node logic adjustment;
- Release and Application: After the development is completed, select the release path (such as MCP Server and Http application), and the agent can be used for personal use, team collaboration, or public release.
With its characteristics of “full openness, low threshold, and strong functions”, Xingchen Agent has brought new possibilities to the field of agent development. It not only frees developers from the constraints of technology and resources but also enables agent applications to quickly penetrate life, the workplace, and various industries, promoting the popularization of intelligent innovation. Whether it is an individual enthusiast who wants to realize ideas or an enterprise seeking digital transformation, they can find a development method suitable for themselves on the Xingchen Agent platform and start a new journey of agent development.
