logo
Free, unlimited AI code reviews that run on commit
git-lrc git-lrc GitHub Install Now We'd appreciate a star git-lrc - Free, unlimited AI code reviews that run on commit | Product Hunt git-lrc - Free, unlimited AI code reviews that run on commit | Product Hunt

mcp-steampipe

Bridge AI models with the Steampipe tool to enable seamless execution of SQL queries on various data sources. Retrieve structured results and simplify data access for AI-driven insights within workflows.

Author

mcp-steampipe logo

b0ttle-neck

MIT License

Quick Info

GitHub GitHub Stars 1
NPM Weekly Downloads 0
Tools 1
Last Updated 2026-02-19

Tags

databasesdatabaseworkflowssecure databasedatabases securedatabase access

Steampipe MCP

This is a simple steampipe MCP server. This acts as a bridge between your AI model and Steampipe tool.

Pre-requisites

  • Python 3.10+ installed.
  • uv installed (my fav) and mcp[cli]
  • Steampipe installed and working.
  • Steampipe plugin configured (e.g., github) with necessary credentials (e.g., token in ~/.steampipe/config/github.spc).
  • Any LLM supporting MCP. I am using Claude Here.
  • Node.js and npx installed (required for the MCP Inspector and potentially for running some MCP servers).

Running MCP Interceptor

This is an awesome tool for testing your if your MCP server is working as expected - Running the Interceptor npx -y @modelcontextprotocol/inspector uv --directory . run steampipe_mcp_server.py - A browser window should open with the MCP Inspector UI (usually at http://localhost:XXXX). - Wait for the "Connected" status on the left panel. - Go to the Tools tab. - You should see the run_steampipe_query tool listed with its description. - Click on the tool name. - In the "Arguments" JSON input field, enter a valid Steampipe query:

{
  "query": "select name, fork_count from github_my_repository "
}
  • execute and view the json results

Running the tool

Pretty straightforward. Just run the interceptor and make sure the tool is working from the directory. Then add the server configuration to the respective LLM and select the tool from the LLM. Screenshot 2025-04-06 at 11 53 23 PM Screenshot 2025-04-06 at 11 55 21 PM

TroubleShooting

  • If the tool is not found in the interceptor then that means @mcp.tool() decorator has some issue.
  • Execution error - Look at the "Result" in the Inspector and the server logs (stderr) in your terminal. Did Steampipe run? Was there a SQL error? A timeout? A JSON parsing error? Adjust the Python script accordingly.
tail -f ~/Library/Logs/Claude/mcp.log
tail -f ~/Library/Logs/Claude/mcp-server-steampipe.log

Security Risk Claude blindly executes your sql query in this POC so there is possibility to generate and execute arbitary SQL Queries via Steampipe using your configured credentials.

See Also

`