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GPT Researcher

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Conducts autonomous, in-depth research by exploring and validating multiple sources to provide relevant and up-to-date information.

🔥🔥🔥🔥✓ VerifiedAccount requiredNeeds API keys
#email#automation#cloud#devops#git#search#maps#finance

🔍 GPT Researcher MCP Server

Why GPT Researcher MCP?

While LLM apps can access web search tools with MCP, GPT Researcher MCP delivers deep research results. Standard search tools return raw results requiring manual filtering, often containing irrelevant sources and wasting context window space.

GPT Researcher autonomously explores and validates numerous sources, focusing only on relevant, trusted and up-to-date information. Though slightly slower than standard search (~30 seconds wait), it delivers:

  • ✨ Higher quality information

  • 📊 Optimized context usage

  • 🔎 Comprehensive results

  • 🧠 Better reasoning for LLMs

💻 Claude Desktop Demo

https://github.com/user-attachments/assets/ef97eea5-a409-42b9-8f6d-b82ab16c52a8

🚦 Transport Modes & Best Practices

The GPT Researcher MCP server supports multiple transport protocols and automatically chooses the best one for your environment:

Transport Types

Transport Use Case When to Use STDIO Claude Desktop, Local MCP clients Default for local development SSE Docker, Web clients, n8n integration Auto-enabled in Docker Streamable HTTP Modern web deployments Advanced web deployments

Automatic Detection

The server automatically detects your environment:

Copy & paste — that's it
# Local development (default)
python server.py
# ➜ Uses STDIO transport (Claude Desktop compatible)

# Docker environment 
docker run gptr-mcp
# ➜ Auto-detects Docker, uses SSE transport

# Manual override
export MCP_TRANSPORT=sse
python server.py
# ➜ Forces SSE transport

Environment Variables

Variable Description Default Example MCP_TRANSPORT Force specific transport stdio sse, streamable-http DOCKER_CONTAINER Force Docker mode Auto-detected true

Configuration Examples

For Claude Desktop (Local)

Copy & paste — that's it
// ~/Library/Application Support/Claude/claude_desktop_config.json
{
 "mcpServers": {
 "gpt-researcher": {
 "command": "python",
 "args": ["/absolute/path/to/server.py"],
 "env": {
 "..."
 }
 }
 }
}

For Docker/Web Deployment

Copy & paste — that's it
# Set transport explicitly for web deployment
export MCP_TRANSPORT=sse
python server.py

# Or use Docker (auto-detects)
docker-compose up -d

For n8n MCP Integration

Copy & paste — that's it
# Use the container name as hostname
docker run --name gptr-mcp -p 8000:8000 gptr-mcp

# In n8n, connect to: http://gptr-mcp:8000/sse

Transport Endpoints

When using SSE or HTTP transports:

  • Health Check: GET /health

  • SSE Endpoint: GET /sse (get session ID)

  • MCP Messages: POST /messages/?session_id=YOUR_SESSION_ID

Best Practices

  • Local Development: Use default STDIO for Claude Desktop

  • Production: Use Docker with automatic SSE detection

  • Testing: Use health endpoints to verify connectivity

  • n8n Integration: Always use container networking with Docker

  • Web Deployment: Consider Streamable HTTP for modern clients

Integrating with Claude

You can integrate your MCP server with Claude using:

Claude Desktop Integration - For using with Claude desktop application on Mac

For detailed instructions, follow the link above.

💻 Claude Desktop Integration

To integrate your locally running MCP server with Claude for Mac, you'll need to:

  • Make sure the MCP server is installed and running

  • Configure Claude Desktop:

  • Locate or create the configuration file at ~/Library/Application Support/Claude/claude_desktop_config.json

  • Add your local GPT Researcher MCP server to the configuration with environment variables

  • Restart Claude to apply the configuration

⚠️ Important: Environment Variables Required

Claude Desktop launches your MCP server as a separate subprocess, so you must explicitly pass your API keys in the configuration. The server cannot access your shell's environment variables or .env file automatically.

Configuration Example

Copy & paste — that's it
{
 "mcpServers": {
 "gptr-mcp": {
 "command": "python",
 "args": ["/absolute/path/to/your/server.py"],
 "env": {
 "OPENAI_API_KEY": "your-actual-openai-key-here",
 "TAVILY_API_KEY": "your-actual-tavily-key-here"
 }
 }
 }
}

Security Note

🔒 Your Claude Desktop config contains sensitive API keys. Protect it:

Copy & paste — that's it
chmod 600 ~/Library/Application\ Support/Claude/claude_desktop_config.json

Never commit this file to version control.

Alternative: Environment Variable Script

For better security, create a wrapper script:

run_gptr_mcp.sh:

Copy & paste — that's it
#!/bin/bash
source /path/to/your/.env
python /absolute/path/to/server.py

Then use it in Claude Desktop:

Copy & paste — that's it
{
 "mcpServers": {
 "gptr-mcp": {
 "command": "/absolute/path/to/run_gptr_mcp.sh"
 }
 }
}

For complete step-by-step instructions, see the Claude Desktop Integration guide.

NVIDIA (NVDA) Current Status

Recent Stock Performance

  • Current price: $942.89 (as of my research)
  • YTD performance: +90.4%
  • 52-week range: $460.30 - $974.00
  • Market cap: ~$2.32 trillion

Recent Key Developments

  1. Blackwell AI Platform: At GTC 2024, NVIDIA unveiled the Blackwell architecture, their next-generation AI chip platform promising 4x performance improvement over Hopper. Major cloud providers (AWS, Google, Microsoft) have already committed to integrating Blackwell.

  2. Q1 FY2025 Earnings (May 2024):

  • Revenue: $26.0 billion (+262% YoY)
  • Data Center revenue: $22.6 billion (+427% YoY)
  • Gross margin: 78.4%
  • Announced 10-for-1 stock split effective June 7, 2024
  1. Supply Chain Expansion: Increased investments in manufacturing capacity with TSMC to address ongoing chip shortages for their high-demand AI GPUs.

Analyst Consensus

  • Strong Buy consensus with 37 analysts rating it "Buy," 5 "Hold," and 0 "Sell"
  • Average price target: $1,042 (post-split adjusted: $104.20)
  • Key bull thesis: Continued AI infrastructure spending and NVIDIA's dominant position in AI chips
  • Key bear concerns: Valuation, potential competition from AMD, Intel, and custom silicon from tech giants

Industry Position

  • Dominant in AI GPU market with estimated 80-90% market share
  • Expanding ecosystem through CUDA software platform and industry partnerships
  • Diversifying beyond chips with DGX Cloud, AI software platforms, and automotive solutions
Copy & paste — that's it

## 👣 Next Steps

- Explore the [MCP protocol documentation](https://docs.anthropic.com/claude/docs/model-context-protocol) to better understand how to integrate with Claude 

- Learn about [GPT Researcher's core features](https://docs.gptr.dev/docs/gpt-researcher/getting-started/introduction) to enhance your research capabilities 

- Check out the [Advanced Usage](https://docs.gptr.dev/docs/gpt-researcher/mcp-server/advanced-usage) guide for more configuration options

## 📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

## 📞 Support / Contact

- [Community Discord](https://discord.gg/QgZXvJAccX) 

- Email: [[email protected]](https://github.com/assafelovic/gptr-mcp/blob/master/mailto:assaf.elovic@gmail.com) 

 
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