What are MCP, Fellou, Manus, Browser, etc.? What are the differences between them and pure AI big models? How to choose?

To understand these new tools, it is important to first understand a few core concepts that form the foundation of these powerful AI applications.

1. MCP (Universal Socket): A protocol that connects everything You can think of MCP (Multi-Capability Protocol) as  the USB-C port that everyone has now . Its core design concept is to lower the integration threshold, allowing developers to easily connect various large models with external tools (such as search engines, databases, office software, etc.) through standardized interfaces. Simply put, MCP is the "universal socket" that allows platforms such as Manus and Fellou to seamlessly connect to components such as Browser, Agent, and Workflow, allowing AI capabilities to be flexibly expanded.

   
   

2. Agent: The "brain" and "executor" of AI Agent is an AI program with the ability to autonomously understand, plan, make decisions, and execute. It is like a "digital brain" that can understand your instructions and then mobilize various tools to complete the task.

• For example, Manus  adopts a multi-agent architecture, with some agents responsible for planning tasks, some responsible for calling tools to execute, and some responsible for monitoring results, and everyone works together.
  
  

• Browser: The "eyes" and "hands" of AI The Browser here is not the ordinary browser we use for surfing, but an "action tool" designed specifically for AI. It allows AI to "see" web page content and "operate" network applications.

• In  Manus  , Browser is one of the tools that Agent uses to perform tasks (such as accessing web pages and crawling data).
• In  Fellou  , the Browser itself is the AI's working platform, and through the "shadow window", the Agent can operate in an independent environment without disturbing you.
  
  

• Workflow: The “assembly line” and “orchestrator” of tasks Workflow refers to the execution process and step arrangement of tasks. It ensures that when AI performs complex tasks, each link can be carried out in an orderly and efficient manner.

• Manus
   The workflow is planned by the Agent itself. You give instructions and it decides what to do.
• Fellou
   It uses its Eko framework to optimize workflow, support parallel processing of tasks, and improve efficiency.
  
  

To summarize : MCP is the underlying connection protocol, Agent is the core executor, Browser is the tool for Agent to interact with the network world, and Workflow is the process that guides Agent on how to complete tasks step by step.



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Baidu Xinxiang, Manus, Fellou, Zhipu AutoGLM Overview

Now that we know the basic components, let’s take a look at some of the most popular AI applications:

• Manus (the world's first universal AI butler): It is an AI program that can complete complex tasks autonomously. For example, if you ask it "help me analyze Tesla stocks", it will automatically break down the task: search for financial reports, analyze market sentiment, and finally generate a complete report with charts. Core features: direct delivery of results, not just chat suggestions.

  
  

• Fellou (the world's first mobile browser): This is a "browser that does work". You only need to say "find the highest-rated graphics card on Amazon and add it to the shopping cart", and it will automatically log in, filter, and add to the cart, without manual work. Core features: AI capabilities are deeply integrated with the browser, and the execution speed is extremely fast (processing similar tasks 4 times faster than Manus).

  
  

• Baidu Xinxiang (Scenario-based Execution AI Example): It can be seen as an intelligent entity composed of "big model + specific scenario + tool". It focuses on specific tasks, such as education, creation, etc., and provides a closed-loop service from demand to results. We will use the example of it generating courseware to explain it in detail later.

  
  

• Zhipu AutoGLM (Deep Thinking and Technical Execution): This tool excels in technical creativity and complex logic processing. Its GLM-Z1-Rumination model supports dynamic verification and self-correction, and can directly operate local files and call APIs.



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Essential difference: “talking” chat AI vs “hands-on” execution AI

This may be the question that everyone is most concerned about: What is the difference between these new AIs and the conversational AIs such as ChatGPT and Doubao that we commonly use?

The answer is: the leap from “talking” to “doing”!

Let me illustrate this with an example: suppose you need to design a courseware to explain linear equations of one variable.

• If using conversational AI (taking Doubao as an example):

1. You type:
    “Design a courseware to explain linear equations of one variable”.
2. AI Output:
    A text lesson plan (about a few hundred words) that includes teaching objectives, key points, and analysis of examples. A PPT outline may be given, but you need to open PowerPoint and make it yourself. Interactive questions? Sorry, it can't do that, you have to find the tools yourself.
3. result:
    What you get is text content, which is a long way from a complete, directly usable courseware. You can expect to spend more than half an hour on manual operation.
   
   

• If you use executive AI (taking Baidu Xinxiang as an example):

• Task breakdown:
   The system automatically breaks down the tasks into knowledge point sorting, lesson plan writing, PPT design, and interactive question generation.
• Tool call (via MCP):
• Dynamic Validation:
   The system will also check the logic of the question to ensure that the equation has a unique solution.
• Call the educational resource library to capture the key points of the textbooks and generate a mind map of knowledge points.
• Content generation agent writes lesson plans containing cases, steps, and exercises.
• PPT Design Agent automatically formats and inserts animations and formulas based on the lesson plan.
• The interactive question agent generates multiple-choice questions and embeds the online answer link.
1. You type:
    “Design a courseware to explain linear equations of one variable”.
2. AI Execution:
3. result:
    You will directly get a compressed package containing PPT, lesson plans, and interactive questions, which can even be synchronized to your network disk and receive SMS notifications. No operation required, and you can get the results directly!
   
   

To sum up: Baidu Xinxiang, Fellou, Manus, Zhipu AutoGLM and other executive AI are essentially agents composed of " big models + scenarios + tools ". They are based on different big models (such as Wenxin, GLM, etc.), call external resources through interfaces such as MCP, focus on specific tasks, and provide closed-loop services from "demand to results".

Pure large models (such as Doubao and ChatGPT) are general capabilities at the bottom layer, focusing more on text interaction and information provision, and users are required to handle the subsequent implementation steps by themselves. The two are the relationship between " basic capabilities " and " scenario-based applications ", and MCP is an important technical bridge connecting the two.




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Content creator, how do I choose?

For content creators with strong creativity and high personalization needs, the choice of AI depends on three core dimensions: task type, tool integration capabilities, and creative freedom .

Structured tasks (such as report generation, data visualization, standard courseware production):

• Preferred: Manus or Baidu Xinxiang.
• reason:
   They can quickly deliver standardized results through preset processes and tool calls. Manus emphasizes the collaboration of multiple agents to complete complex reports; Baidu Xinxiang has mature templates and resources for specific scenarios (such as marketing materials and educational courseware).
• optimization:
   If you need to enhance creativity, after Manus/Xin Xiang generates a basic report, you can use pure large models such as Doubao to polish it or add personalized cases.




Unstructured creativity (such as storytelling, art design, new media copywriting):

• Preferred: Pure large models (such as Doubao) or Fellou.
• reason:
• Bean bag:
   It provides a high degree of freedom in generation. For example, if you input "generate 8 storyboards of couples meeting and falling in love in the style of Wong Kar-wai's movies", Doubao can quickly output high-quality pictures and support style adjustment and batch output.
• Fellou:
   It supports dynamic adjustments during the creation process and can collaborate across platforms. For example, you can first use Doubao to generate a draft copy, and then use Fellou to call Canva and other design tools to optimize the layout.




Technical creativity (such as code generation, data analysis, and academic research assistance):

• Priority: Zhipu AutoGLM.
• reason:
   Its deep thinking model and powerful tool calling capabilities (operating local files, API) can handle complex logic. For example, if you enter "generate Python crawler code and save the results to Excel", AutoGLM can complete it in one stop.
• Limitations:
   There is limited support for non-technical creativity (such as art design), and it may be necessary to combine pure AI large models such as Doubao to supplement visual content.




Cross-platform collaboration and dynamic adjustment (such as cross-border marketing plans, complex project management):

• First choice: Fellou.
• reason:
   As a mobile browser, it can directly call platforms such as LinkedIn and Notion, which is suitable for creators who need multi-platform collaboration. Its active intelligence can also analyze user behavior to predict needs, and its multi-threaded task processing capabilities greatly improve efficiency (the average time is only 3.7 minutes, which is faster than similar products).


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Advanced gameplay: Use in combination to double the effect!

Smart creators never limit themselves to a single tool, but learn to use a combination of tools:

• Agent + Large Model:

• process:
   Use Manus or Baidu Xinxiang to complete the structural part (such as data collection and basic framework construction). Then, use pure large models such as Doubao to generate personalized content (such as wonderful stories and unique visual styles), and then integrate it into the output of the intelligent agent.
• Examples:
   To produce the company brochure, Manus generated product specifications and diagrams, Doubao created an engaging brand story and visual design, and Fellou assisted with typesetting and export.

• Multi-agent collaboration (future trend):

• Scenario:
   Large projects, such as film productions.
• Division of labor idea:
   Baidu Xinxiang generates script frameworks and storyboard templates; Fellou uses the film and television resource library to select actors and scenes; Zhipu AutoGLM analyzes market data to optimize budgets. Through the MCP protocol, these intelligent agents are expected to achieve seamless collaboration.


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Pitfalls and solutions: Common problems and solutions

• Creative homogeneity:

• reason:
   Over-reliance on templates or preset processes.
• solve:
   After generating basic content using large models such as Doubao, personalized adjustments are made through iterative prompt words (such as "add more emotional elements"); in Fellou, the "active intelligence" function is used to obtain differentiated suggestions.
  
  

• Tool call failed:

• reason:
   Insufficient API permissions or incompatible tool.
• solve:
   Check tool permissions in Baidu Xinxiang or Zhipu AutoGLM; if you encounter compatibility issues, try Fellou's "Shadow Workspace" to execute in an isolated environment.
  
  

• Data security risks:

• reason:
   Agents may have access to sensitive data.
• solve:
   Set permissions granularly in enterprise-level platforms (such as Qianfan AppBuilder); for highly confidential content, give priority to using locally deployed tools (such as Zhipu AutoGLM virtual machine version).


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Summary: Your AI toolbox, your choice!

The world of AI is changing with each passing day, but the core logic and application scenarios are becoming clearer. Whether it is an executive AI like Baidu Xinxiang, Fellou, and Manus, or a conversational AI like Doubao and ChatGPT, they all have their own advantages and applicable scenarios.

• Pursuing efficiency and standardized delivery:
   Choose Baidu Xinxiang or Manus.
• Pursue high degree of freedom and personalized creativity:
   Rely on pure large models such as Doubao, supplemented by Fellou for implementation.
• Facing complex collaboration and cross-platform tasks:
   Fellou is the right-hand man.
• Deeply cultivate technical creativity:
   Zhipu AutoGLM is better.

The most important thing is to understand the nature of these tools and select and combine them according to your specific needs. The key to choosing AI tools is to match them with your needs . Whether it is the efficient delivery of executive AI or the flexible creativity of conversational AI, they can play their value in different scenarios. Be bold and try, and let AI become a powerful helper to improve your efficiency and unleash your creativity!