Chlorpromazine MCP Server: Your Antidote to LLM Hallucinations

In the rapidly evolving landscape of AI-driven development, the allure of “vibe coding”—where developers embrace the spontaneous creativity of Large Language Models (LLMs)—is undeniable. However, this freewheeling approach can often lead to unpredictable and, at times, downright problematic results: the dreaded LLM hallucination. Enter Chlorpromazine MCP Server, a tongue-in-cheek yet remarkably practical tool designed to ground your LLMs in reality and prevent them from going off the rails.

Inspired by the antipsychotic medication of the same name, Chlorpromazine MCP Server acts as a “trip killer” for your AI agents. It’s a Model Context Protocol (MCP) server implementation that equips your LLMs with the ability to access and verify information, ensuring they stay tethered to documented facts and avoid veering into the realm of fabricated data.

What is MCP and Why Does it Matter?

Before diving deeper, let’s clarify the core concept: MCP. MCP, or Model Context Protocol, is an open protocol designed to standardize how applications provide context to LLMs. Think of it as a universal language that allows different AI models to seamlessly access and interact with external data sources, tools, and APIs. An MCP server acts as the intermediary, handling requests from LLMs and providing them with the necessary information to perform their tasks accurately and reliably.

Use Cases: When Chlorpromazine MCP Server Shines

• Vibe Coding Sanity: The primary use case, as the creator intended, is to inject a dose of reality into vibe coding sessions. When your LLM starts generating code that seems too good to be true (or just plain wrong), Chlorpromazine steps in to verify the logic and syntax against official documentation.
• Hallucination Prevention: Any application that relies on LLMs for generating factual content can benefit. Whether you’re building a chatbot, a content creation tool, or a data analysis platform, Chlorpromazine helps ensure the information presented is accurate and verifiable.
• Documentation-Driven Development: Enforce a culture of referencing documentation within your AI-powered workflows. By integrating Chlorpromazine, you encourage your LLMs (and your developers) to consult authoritative sources before making assumptions or generating code.
• Enhanced AI Agent Reliability: When integrated into an AI Agent workflow, it ensures that the agent can reliably access and utilize external tools and APIs. This is crucial for tasks such as data retrieval, code execution, and real-world interaction.

Key Features: Your Arsenal Against AI Delusions

• MCP-Compliant Prompts: Adheres to the Model Context Protocol, ensuring seamless integration with MCP-compatible LLMs and tools.
• kill_trip Tool: This tool leverages the SerpAPI to perform documentation searches. It’s triggered when the user expresses doubt, accuses the agent of being wrong, or uses phrases suggesting the agent is hallucinating. This tool is great to verify against official sources.
• sober_thinking Tool: This tool reads project files like .env, README.md, and CHANGELOG to provide grounded information about the project’s current status and configuration. This helps the agent avoid making incorrect assumptions.
• Health Check Endpoint: A /healthz endpoint for monitoring the server’s status and ensuring its availability.
• API Endpoints: Provides standard MCP endpoints for listing and retrieving prompts and tools, as well as calling specific tools.

Technical Deep Dive: How Chlorpromazine Works

At its core, Chlorpromazine MCP Server is a Node.js application built using the @modelcontextprotocol/sdk. It leverages the power of ES Modules for modularity and maintainability. The server uses a native Node.js http.Server for robust request handling and lifecycle management, with the MCP transport seamlessly integrated.

The kill_trip tool uses the SerpAPI, a powerful search engine API, to retrieve relevant documentation based on the user’s query. The tool is designed to be triggered when the user expresses frustration or disbelief in the agent’s output. This ensures that the agent is constantly verifying its claims against authoritative sources.

The sober_thinking tool reads the project’s configuration files to gain a clear understanding of the current environment. This prevents the agent from making assumptions based on outdated or incorrect information.

Integration with UBOS: Elevating AI Agent Development

Chlorpromazine MCP Server finds a natural home within the UBOS ecosystem. UBOS is a full-stack AI Agent development platform designed to empower businesses to build and deploy AI Agents across various departments. By integrating Chlorpromazine into your UBOS-powered AI Agents, you can:

• Orchestrate Reliable AI Agents: Ensure that your AI Agents are grounded in factual information, reducing the risk of hallucinations and errors.
• Connect to Enterprise Data with Confidence: Verify the accuracy of data retrieved from your enterprise systems, preventing agents from making decisions based on flawed information.
• Build Custom AI Agents with Enhanced Accuracy: Equip your custom AI Agents with the ability to self-verify their outputs, leading to more reliable and trustworthy results.
• Create Robust Multi-Agent Systems: Coordinate multiple AI Agents with confidence, knowing that each agent is capable of verifying its own knowledge and contributing accurate information to the collective decision-making process.

In essence, Chlorpromazine MCP Server acts as a crucial safety net, ensuring that your AI Agents remain grounded, reliable, and trustworthy. It’s the perfect antidote to the unpredictable nature of LLM hallucinations, allowing you to embrace the power of AI without sacrificing accuracy and control.

Deployment and Security Considerations

Deploying Chlorpromazine MCP Server is straightforward, especially on platforms like Smithery.ai. The project is designed to be easily deployed from a GitHub repository, with environment secrets managed through the platform’s dashboard.

However, security is paramount. The server should not be exposed directly to the public internet without proper security measures. Two recommended approaches are:

1. Deploy behind an API gateway to manage traffic and enforce security policies.
2. Enable API key authentication by setting the API_KEY environment variable, requiring clients to authenticate before accessing the server’s endpoints.

By prioritizing security, you can ensure that your Chlorpromazine MCP Server remains a reliable and trustworthy component of your AI infrastructure.

Conclusion: Embrace AI with Grounded Confidence

Chlorpromazine MCP Server is more than just a clever name; it’s a practical tool for taming the wild side of LLMs. By providing a mechanism for verifying information and grounding AI agents in reality, it empowers developers to embrace the power of AI with confidence. Whether you’re engaging in vibe coding or building mission-critical AI applications, Chlorpromazine MCP Server is your ally in the fight against AI hallucinations.

Integrate it with UBOS, and you’ll unlock even greater potential for building reliable and trustworthy AI Agents that drive real business value.