Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Benchmark MCP Server Compare my retail store's $150,000 annual revenue against the industry average"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server with Industry Benchmarking Tool - Compatible with both Claude and ChatGPT.
š Industry Benchmarking Tool: Compare company metrics against industry averages
šØ Interactive Widget: Visual bar chart comparison (MCP Apps)
š Dual Transport: Supports both SSE and Streamable HTTP
ā Cross-Platform: Works with Claude.ai and ChatGPT
Related MCP server: GOD MODE INTEL MCP Server
# Install dependencies
poetry install
# Start server
poetry run python main.py# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install dependencies
pip install mcp>=1.26.0 uvicorn pydantic
# Start server
python main.pyEndpoint | Transport | Use For |
| SSE | Claude, ChatGPT (via ngrok) |
| Streamable HTTP | ChatGPT native |
| Streamable HTTP | Alias |
# Start ngrok
ngrok http 8000
# Use the ngrok URL in Claude/ChatGPT:
# https://your-ngrok-url/sseclaude-mcp-app/
āāā app/
ā āāā service/
ā ā āāā mcp_server.py # FastMCP instance
ā ā āāā data/ # Mock benchmark data
ā ā āāā tools/ # MCP tools
ā ā ā āāā benchmarking_tool.py
ā ā ā āāā benchmarking_widget.py
ā ā āāā widgets/ # HTML widgets
ā ā āāā benchmarking_widget.html
āāā common/
ā āāā config.py # Configuration
āāā main.py # Entry point
āāā pyproject.toml # Poetry config
āāā README.md"How does my restaurant's $45,000 yearly profit compare to the industry average in California?"
"Compare my retail business revenue of $500,000 against industry benchmarks in Texas"
"Benchmark my healthcare company's monthly income of $80,000 against regional averages"
"How does my construction company in NY with $600,000 annual revenue compare?"
MIT
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16 AI-native tools with dual SSE + streamable-http transport. Free tier available.
AI research on companies and industries ā one MCP tool per research domain.
SEC EDGAR financial data for AI agents ā revenue, margins, filings, company comparisons.
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