Overview of Tavil mCP Server and Deep Research

Introduction

• Discussing the new Tavil mCP server and its significance.
• Overview of T: A search and scraping tool for Large Language Models (LLMs).
• Comparison between Tavil and community-created mCP servers.

Comparison of Search Tools

• Brave Search: Effective for broad internet searches.
• Tavil (T): Provides detailed and quick responses, especially for deep research tasks.

OpenAI Developments

• Recent releases by OpenAI: Sora, tasks, operator, and deep research.
• Deep Research by OpenAI: Highly effective, detailed, reduces hallucinations compared to other LLMs.
• Operator and Tasks: Limited impact compared to initial expectations.

Practical Example: Creatine Research

• Personal inquiry into the safety of creatine for someone immunosuppressed.
• Deep Research’s detailed findings on creatine for cancer recovery.
• Verification of deep research outputs against various sources showed high accuracy.

Workflow Using Deep Research

• Using OpenAI’s Deep Research to obtain a detailed report.
• Workflow to condense information using Notebook LM for podcast creation.
• Benefits of transforming detailed research papers into consumable audio content.

Discussion on Cost and Replication

• Current limitations of replicating OpenAI’s Deep Research quality.
• Anticipation of open-source alternatives in the future.

Tavil mCP Server Exploration

• Release of Tavil’s official mCP server.
• Features: Search and extract tools hosted on GitHub.
• Usage of API credits: Tavil offers a free plan with 1,000 credits.

Custom Instructions for Deepest Research

• Integration of Tavil and Brave Search with sequential thinking in Claw desktop.
• Setup process: Adding Tavil mCP to the config file in VS Code.

Project: Deepest Research with Claw

• Utilization of custom instructions for deep research.
• Combination of sequential thinking, Brave Search, and Tavil for research.
• Emphasis on clarifying questions and confirming research plans.

Results and Reflection

• Attempt to replicate OpenAI’s Deep Research outputs with limitations.
• Discussion on the quality and quantity of research outputs using Tavil and Brave.

Conclusion

• Encouragement to explore OpenAI’s deep research and engage with the Tavil mCP server.
• Call for feedback and suggestions on research topics or custom instructions improvements.
• Invitation to subscribe and engage with further content.