Mcp Delete

Overview

The @qpd-v/mcp-delete server extends the Model Context Protocol ecosystem by providing a secure, AI‑driven file deletion capability. It enables Claude and other MCP‑compatible assistants to remove files directly from the host environment, a task that traditionally requires manual intervention or separate scripts. By exposing a simple tool, the server allows conversational agents to perform destructive actions with confidence, leveraging built‑in safety checks and detailed error reporting.

Why Developers Need It

In many AI workflows—automated build pipelines, data preprocessing, or interactive coding assistants—there is a recurring need to clean up temporary files or discard obsolete artifacts. Without an MCP server, developers must write custom scripts or rely on the host OS’s command line, interrupting the conversational flow. MCP Delete bridges this gap by offering a declarative API: “Please delete ” becomes an instant, traceable operation that the assistant can confirm or abort if necessary. This streamlines iteration cycles and reduces context switching for developers.

Core Features Explained

• Dual Path Support: Accepts both relative and absolute file paths, making it flexible in diverse directory structures.
• Smart Path Resolution: The server automatically attempts multiple resolution strategies—exact path, relative to the working directory, and relative to a configured base directory—ensuring the file is located even when the user’s reference is ambiguous.
• Safety First: Before deletion, it verifies file existence and reports any issues with comprehensive diagnostic messages that include the attempted resolution steps.
• Cross‑Platform Compatibility: Works seamlessly with Claude Desktop on Windows and macOS, as well as with VSCode extensions like Roo Cline.
• Extensible Toolset: While the primary tool is , the server’s architecture allows future expansion (e.g., batch deletion, directory removal) without altering client logic.

Real‑World Use Cases

• Continuous Integration: An AI assistant can automatically clean up build artifacts after a test run, keeping the workspace tidy.
• Data Science Pipelines: Remove intermediate datasets once downstream steps complete, preventing storage bloat.
• Interactive Coding Environments: Developers can ask the assistant to delete a temporary script file while experimenting, keeping their project directory organized.
• Deployment Scripts: In a serverless context, an AI can delete temporary logs or cache files after deployment to free resources.

Integration with AI Workflows

Clients register the MCP Delete server in their configuration files, after which any supported assistant can invoke the tool via natural language. The assistant translates a user request into an MCP command, sends it over stdio, and receives a structured response that confirms success or details errors. Because the server communicates using the same protocol as other tools (e.g., , ), developers can compose complex workflows that combine file manipulation, data retrieval, and computation without leaving the conversational interface.

Unique Advantages

• Safety‑oriented Design: By validating paths and providing clear diagnostics, the server mitigates accidental deletions—a critical concern when AI assistants operate with elevated privileges.
• Intelligent Resolution: The multi‑step path resolution reduces friction for users, especially in large projects where file locations can be nested or ambiguous.
• Zero‑Code Interaction: Developers do not need to write scripts or shell commands; the assistant handles the logic, allowing focus on higher‑level problem solving.

In summary, MCP Delete empowers AI assistants to perform file deletions reliably and safely, enhancing developer productivity across build pipelines, data workflows, and interactive coding sessions.