While traditional LLMs excel at answering questions, they fall short when it comes to executing real-world tasks. General Bots solves this problem by implementing the Model Communication Protocol (MCP) through BASIC-powered tools that bridge the gap between AI understanding and actionable outcomes.
General Bots uses BASIC syntax to implement the Model Communication Protocol (MCP), creating a simple yet powerful way to define structured interactions between users and systems. This approach makes creating tools as simple as writing a few lines of BASIC code.
BASIC tools seamlessly integrate with CSV files and databases, providing persistent storage for enrollment data, student records, and other critical information. This allows for data-driven workflows that extend beyond the LLM's context window.
MCP's structured parameter collection ensures that all required information is gathered properly. With typed parameters and validation rules, the system guarantees data integrity while providing helpful error messages when needed.
Unlike standard LLMs that can only provide information, General Bots BASIC tools can trigger actual system actions - from registering students and processing payments to generating reports and sending notifications - all within the conversation flow.
' BASIC MCP Tool for Course Enrollment
PARAM name AS string LIKE "Maria Silva"
DESCRIPTION "Required full name of the student."
PARAM birthday AS date LIKE "15/07/2002"
DESCRIPTION "Required birth date in DD/MM/YYYY format."
PARAM email AS string LIKE "maria.silva@example.com"
DESCRIPTION "Required email address for communications."
PARAM personalId AS integer LIKE "12345678900"
DESCRIPTION "Required Personal ID number (only numbers)."
PARAM program AS string LIKE "Computer Science"
DESCRIPTION "Required program name to enroll in."
PARAM semester AS string LIKE "2025-1"
DESCRIPTION "Required semester code."
DESCRIPTION "This tool handles the student enrollment process.
When executed, it collects all required information and registers
the student in the specified program."
' Data validation example
VALIDATE email CONTAINS "@" "Please provide a valid email address."
VALIDATE program IN LOAD("programs.csv", "name") "Program not found."
' Save enrollment data
SAVE "enrollments.csv", id, name, birthday, email, personalId, program, semester
RETURN "Thank you {{name}}! Your enrollment in {{program}} for semester {{semester}}
has been successfully processed. You will receive a confirmation email at {{email}}."Both formats achieve the same goal - structured enrollment data collection and processing. General Bots converts BASIC tools into MCP format behind the scenes, creating a seamless integration between your LLMs and backend systems.
The LLM recognizes the user's intention to enroll in a program
The appropriate BASIC tool is selected and executed
The system collects all required information from the user
The collected information is stored in a CSV file or database
The system provides a confirmation message to the user
| Feature | Traditional LLM | LLM + BASIC/MCP Tools |
|---|---|---|
| Data Storage | ❌ No persistent storage | ✅ CSV/database storage |
| Structured Input | ⚠️ Inconsistent extraction | ✅ Typed parameters with validation |
| System Actions | ❌ Cannot perform actions | ✅ Can execute real-world tasks |
| Context Window | ⚠️ Limited by token count | ✅ External data access |
| Audit Trail | ❌ No built-in logging | ✅ Built-in logging capabilities |
| Knowledge | ✅ Broad knowledge base | ✅ Combines knowledge with specialized tools |
| Aspect | Model Context Protocol (MCP) | LLM Tools |
|---|---|---|
| Origin | Developed by Anthropic as an open standard | Popularized by OpenAI's function calling, with various implementations across platforms |
| Structure | Provides a standardized protocol for model-tool interaction | Often platform-specific implementations with varying approaches |
| Implementation | Focused on a consistent schema for tool definitions and interactions | Implementation details vary across different LLM platforms |
| Specificity | Designed specifically for Claude and compatible models | General concept implemented across many LLM platforms |
| Standardization | Aims to create an open, consistent standard | Often proprietary implementations with platform-specific features |
| Tool discovery | Emphasizes dynamic tool discovery | Tool availability often pre-defined in the system |
| Tool registration | Supports dynamic tool registration during conversations | Tools typically registered before conversation starts |
| Framework | More comprehensive framework for tool interaction | Can range from simple function calling to complex systems |
| Documentation | Centralized documentation from Anthropic | Documentation varies by platform/implementation |
| Ecosystem | Developing ecosystem around a consistent standard | Fragmented ecosystem with platform-specific tools |
Both approaches serve similar purposes but differ in implementation details, standardization efforts, and ecosystem approach.
A large university implemented General Bots with BASIC tools to handle their entire enrollment ecosystem, allowing students to interact with a conversational AI to:
A financial institution created a comprehensive customer service system using MCP-based tools to:
While large companies attempt to control the LLM tool market, the future belongs to open standards and implementations. The Model Communication Protocol (MCP) is emerging as a key standard for LLM tool integration, with implementations like ModelScope MCP gaining traction globally.
General Bots takes this a step further by making MCP implementation accessible through simple BASIC syntax - eliminating the complexity while maintaining full compatibility with emerging standards. This means your tools will work across the LLM ecosystem without vendor lock-in.
"Neither Claude nor Microsoft will dictate the market. The future of LLM tools is being built on open standards like MCP, with implementations like General Bots making them accessible to everyone."
— The General Bots Team
Create complex tools with simple BASIC syntax instead of wrestling with complicated JSON structures or learning new programming patterns.
Get everything you need - from dialog management to data storage to integration capabilities - in one comprehensive platform.
Build on open MCP standards that ensure your tools can work across different LLM platforms without being locked into a single vendor.
Set up General Bots on your server or use our cloud hosting options
Set up your data directories and connect your preferred LLM
Create BASIC tools for your specific tasks and workflows
Launch your tool-enhanced LLM system and start engaging users
Let General Bots help you implement MCP tools that bridge your AI with real-world systems. Our team of specialists will analyze your needs and develop a custom implementation plan.
General Bots® LLM and custom AI models.
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