Hey there,
This guide is designed to help you create more efficient, performant projects by integrating MCP Sequential Thinking with the OpenRouter AI API. If you’re new to coding, please take some time to build a solid foundation—having basic code knowledge is essential to get the most out of these strategies knowing this we are able to optimize our code x1000 within our codebase and the project that we will continue working on, this could be a new project or an already made project that we could integrate.
Pages, I’ve done using this whole guide.
We will need the following MCP Servers
Our MCP Section it should be looking like this:
Note: When we add a new MCP server and Cursor explicitly doesn’t update it, make sure to drag the mcp.json into the chat, tell him to add the MCP server. This won’t give you an actual overwrite, so you’ll have to copy the code he’s giving you and paste it into your live version of MCP and save it for it to run.
Suggestion: Developers, add a background check on MCP instead of opening multiple tabs at the same time, make it run in the background.
Introduction
In this Guide, you’ll learn how to:
- Break down tasks: Use MCP Sequential Thinking to decompose complex tasks into manageable pieces.
- Incorporate real-time insights: Execute a web search for the latest updates relevant to your work.
- Enhance your code: Refine your original input through iterative feedback with the OpenRouter AI API.
- Improve overall output: Create a feedback loop that continuously elevates your project performance.
This approach ensures that your initial prompt evolves into a more complete and refined version with each iteration, resulting in an output that’s both efficient and highly effective.
Step-by-Step Integration Tutorial
Step 1: Embrace Sequential Thinking
Start by structuring your project logically:
- Decompose Tasks: Split your project into smaller, manageable sections.
- Sequence Steps: Clearly outline the order in which each task should be executed.
- Identify Dependencies: Recognize which tasks depend on others to prioritize your workflow.
Using the following prompt, we can start our main structure.
Decompose the following [include your task here] into manageable subtasks. For each subtask, list step-by-step instructions. Explicitly identify any dependencies between subtasks to optimize workflow and task prioritization for efficient completion.
Step 2: Integrate Web Searching
Once your tasks are outlined, enhance your plan by:
- Performing a Web Search: Automatically browse the web to gather the latest trends and updates related to your project.
- Updating Context: Use the information gathered to adjust your task breakdown and keep your project relevant.
Using the following prompt, we can start our web search, we can use Brave MCP or Cursor Native Search or DuckDuckGo Search MCP
We are going to begin seeing all the MCP Server adjust, find and search the best output to provide within the codebase chat bubble.
Start a search wether be using Brave or Duck Search [include your task here] and crawl the latest 5 up-to-date information about what was asked, Explicitly identify what it’s needed in order to optimize workflow and task prioritization for efficient completion.
Applied Sequential Thinking + OpenRouter Call
Applied Sequential Thinking + OpenRouter Model Search
Based on the latest research, we are able to get through the latest news and information about what we have given to the AI in order for us to continue optimizing our prompting and project itself.
Step 3: Leverage OpenRouter AI
Now, refine your project with AI-powered insights:
- Initialization:
- Set up your MCP Server for initialization.
- Ensure your configuration file (e.g., .cursor/rules/{rule}.mdc) is set to enforce rules consistently.
- First AI Pass:
- Use OpenRouter AI (e.g., the QWEN 32B:free) to obtain code suggestions and new ideas.
Step 4: Iterative Refinement
Enhance your code further by reapplying sequential thinking:
- Iterative Improvement: Re-prompt OpenRouter AI with your refined input for additional feedback.
- Adaptive Strategy: Adjust your workflow based on AI insights to achieve greater clarity and efficiency.
- Feedback Loop: Continuously update your project using the improved outputs from the AI iterations.
At this point, there’s no need to input any other prompt unless you want to continue, the AGENT itself will continue sequential thinking, over and over.
Ensuring Consistency and Efficiency
Using MCP Servers
- Uniform Application: Confirm that all commands are routed through MCP Server configurations.
- Standardized Settings: Use default MCP methods or adapt your custom integrations when needed.
Delivering on Capabilities
- Enable Sequential Thinking: Activate sequential thinking across all tools to maintain consistent logic.
- Rely on AI-Generated Solutions: Use MCP Server’s QWEN for insightful improvements.
- Streamline Planning: Rigorously use Linear for coherent task management.
Presenting Thoughtful Responses
- Be Immediate and Precise: Keep your responses focused and free of vagueness.
- Document Experimentation: Clearly mark new solutions and document changes for transparency.
- Focus on Security: Emphasize only the essential issues to maintain a secure environment.
Final Thoughts
By integrating MCP Sequential Thinking with OpenRouter AI, you’re setting up a dynamic environment that continuously improves your coding output. Remember to:
- Regularly Use Sequential Thinking: Decompose, sequence, and refine your tasks.
- Engage OpenRouter AI Twice: First for initial setup and then for iterative refinement.
- Follow MCP Guidelines: Adhere strictly to the
cursor/rules/{rule}.mdcsettings for optimal performance.
Tip: This guide is a living document. As you experiment and learn, update your process and refine your strategy to stay on the cutting edge.
These steps ensure your coding environment is primed for efficiency, innovation, and seamless AI integration, ultimately elevating performance and productivity to new heights.
