What benefits do you see from having the agent call a CLI like this via MCP as opposed to just executing the CLI as a shell command and taking action on the stdout?
What benefits do you see from having the agent call a CLI like this via MCP as opposed to just executing the CLI as a shell command and taking action on the stdout?
This is one of the most important questions I see when people recommend an MCP server.
If cursor and Claude code can already run an executable why do I need to add an MCP server in front of it?
I feel like a lot of times it’s, “Because AI”
Few things:
- Security/Speed: I leave "approve CLI commands" on in Cursor. This functions as a whitelist of known safe commands. It only needs to ask if running a non-standard command, 99% of the time it can use tools. It will also verify paths passed by the model are in the project folder (not letting it execute on external files)
- Discoverability: For agents to work well, you need to explain which commands are available, when to use each, parameters, etc. This is a more formal version than a simple AGENTS.md, with typed parameters, tool descriptions, etc.
- Correctness: I find models mess up command strings or run them in the wrong folders. This is more robust than pure strings, with short tool names, type checking, schemas, etc.
- Parallel execution: MCP tools can run in parallel, CLI tools typically can't
- Sharing across team: which dev commands to run can be spread across agents.md, github workflows, etc. This is one central place for the agents use case.
- Prompts: MCP also supports prompts (less known MCP feature). Not really relevant to the "why not CLI" question, but it's a benefit of the tool. It provides a short description of the available prompts, then lets the model load any by name. It's requires much less room in context than loading an entire /agents folder.