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Integrate coding, documents, remote execution, and databases for faster developer automation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AMEVA MCP Toolkit" yet — see the docs or source repo.
Connect to the staging server over SSH, pull the latest Git branch, install dependencies, restart the service, then inspect the last 100 log lines and summarize any issues.
A report with execution results, key log summaries, and any likely deployment issues.
Convert all Markdown documents in this project directory to PDF and list any files that failed along with the reasons.
A conversion summary, generated file locations, and a list of failure reasons.
Connect to the business database, calculate daily new users for the past 30 days, export the results as CSV, and provide a brief analysis of unusual fluctuations.
Statistical results, CSV export details, and a short interpretation of unusual data changes.
Secure file and directory operations for autonomous AI development workflows.
Call tools like weather lookup via MCP with reusable resources and prompts.
Run SQL, APIs, and sandboxed Python for multi-step research and data tasks.
Connect to and operate MCP servers from the command line.
Connect to the mcp API via MCP to extend AI tool capabilities.
Use MCP tools to analyze GitHub repos, calculate, check weather/time, and run commands.