Build Your Own Research Agent with Brave Search+Sequential Thinking MCP Servers

Build Your Own Research Agent with Brave Search+Sequential Thinking MCP Servers
by Yandi Farinango

I've discovered a game-changing combination that's transformed my workflow: Brave Search + Sequential Thinking MCP servers

This setup essentially creates a powerful research AI agent, rivaling capabilities you'd find in premium tools like Perplexity Pro. Let me walk you through how this works and how you can set it up yourself.

TLDR

  • Combine Brave Search + Sequential Thinking MCP servers
  • Create a powerful research agent similar to Perplexity Pro
  • Easy setup with Claude Desktop or any MCP-compatible client
  • Real-time web search and structured analysis capabilities

The Power of Combined MCP Servers

While many developers are familiar with individual MCP servers, the magic happens when you combine them strategically. The Brave Search and Sequential Thinking servers, when used together, create an unstoppable research agent:

  • Brave Search provides comprehensive web access capabilities
  • Sequential Thinking enables structured, multi-step reasoning
  • Together, they allow Claude Desktop (or any MCP compatible LLM Application) to research, analyze, and synthesize information in real-time

Setting Up Your Research Agent

Here's how to get this powerful combination up and running:

Prerequisites

  • Claude Desktop (latest version)
  • Node.js 16 or higher
  • Brave Search API key

Step 1: Configure Brave Search Server

Let's set up the Brave Search and Sequential Thinking MCP Servers. Add the following to your claude_desktop_config.json

{
  "mcp_servers": {
    "brave-search": {
      // NPX command to run the server
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-brave-search"
      ],
      // Environment variables for API authentication
      "env": {
        "BRAVE_API_KEY": "YOUR_BRAVE_API_KEY"
      }
    },
    "sequential-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-sequential-thinking"
      ]
    }
  }
}

Integration and Usage

The real magic happens when you combine these servers in your workflow. Here's what I've found works best:

  1. Research Initialization
    • Start with a clear research question
    • Let Sequential Thinking break it down into manageable steps
    • Use Brave Search to gather relevant information for each step
  2. Analysis Flow
    • Sequential Thinking processes the search results
    • Builds logical connections between pieces of information
    • Generates comprehensive insights based on the gathered data

Pro Tips From My Experience

After using this setup for a while, I've discovered some valuable optimizations:

Query Structuring

  • Let Sequential Thinking refine your search queries
  • Use Brave Search to get get the most up to date information
  • Combine multiple search results for comprehensive coverage

Practical Applications

I've found this setup particularly powerful for:

  • Technical research and documentation
  • Competitive intelligence gathering
  • Technical documentation creation
  • Real-time fact verification

Looking Forward

This combination of MCP servers is just the beginning. As the MCP ecosystem grows, we'll likely see even more powerful combinations emerge. I'm particularly excited about the potential for:

  • Integration with specialized data sources
  • Enhanced reasoning capabilities
  • Local Inference with open source models

Conclusion

The combination of Brave Search and Sequential Thinking MCP servers has fundamentally changed how I interact with AI assistants. It's like having a research assistant who can not only find information but also think through it systematically and present cohesive insights.

Want to see this in action or discuss your own MCP server setup? Feel free to reach out – I'm always excited to explore new possibilities in this space.