mcp-cli
by obraUse the mcp-cli skill to discover MCP server tools, resources, and prompts on demand without permanent integrations. It fits mcp-cli usage for debugging, one-off access, and workflow automation when you already have a server command and want a lightweight guide.
This skill scores 78/100, which means it is a solid but not flawless listing candidate: directory users get enough operational detail to decide to install it, and it clearly supports on-demand MCP discovery and use via the mcp CLI rather than a generic prompt. The documentation is substantial, with valid frontmatter, long-form workflow guidance, examples, and constraints, though it lacks packaged support files and a built-in install command, so adoption still requires some setup confidence.
- Clear triggerability for on-demand MCP server use, including discovery of tools, resources, and prompts.
- Strong workflow content with step-by-step examples for common server types and one-off invocation patterns.
- Good install-decision value because it explains when to use the skill: exploration, debugging, temporary access, and avoiding permanent integrations.
- No install command in SKILL.md, so users must set up the mcp CLI manually before the skill is usable.
- No support files or references/resources/rules assets, which limits external validation and hands-on scaffolding.
Overview of mcp-cli skill
The mcp-cli skill helps you use MCP servers on demand through the mcp command-line tool, so you can discover tools, resources, and prompts without permanently wiring an MCP server into your agent setup. This is useful if you want a lightweight, testable way to probe a server before you commit to a full integration.
What mcp-cli is for
This mcp-cli skill is best for agents and power users who need quick access to MCP capabilities, especially when the real job is “find out what this server can do” rather than “build a long-lived connector.” It fits workflow automation, ad hoc debugging, and short-run tasks where context bloat matters.
When it is a good fit
Use mcp-cli when you already have an MCP server command, URL, or container image and need to inspect what it exposes. It is especially useful for one-off filesystem, GitHub, memory, or HTTP-based servers, and for cases where the server is not pre-configured in your environment.
Main adoption tradeoffs
The biggest value is discovery without setup overhead; the biggest constraint is that you still need a working local mcp binary and a valid server command. If you want fully managed, persistent MCP integrations, this skill is not the right first choice.
How to Use mcp-cli skill
Install mcp-cli and verify the binary
For mcp-cli install, the repository expects the mcp binary at ~/.local/bin/mcp. If it is missing, build it first, then make sure your PATH includes ~/.local/bin:
cd /tmp && git clone --depth 1 https://github.com/f/mcptools.git
cd mcptools && CGO_ENABLED=0 go build -o ~/.local/bin/mcp ./cmd/mcptools
export PATH="$HOME/.local/bin:$PATH"
If the binary is not on PATH, the skill will fail before any discovery happens.
Start from a concrete server command
mcp-cli usage works best when you provide a real server invocation, not a vague goal. Good inputs name the server and how it runs, such as npx -y @modelcontextprotocol/server-filesystem /path/to/allow, docker run ... ghcr.io/github/github-mcp-server, or an HTTPS endpoint. That makes the skill actionable instead of speculative.
Run discovery in the right order
First, ask the skill to enumerate tools with mcp tools <server-command>. If the server supports more than tools, continue with mcp resources <server-command> and mcp prompts <server-command>. This sequence tells you what is available before you try to call anything, which is the core advantage of mcp-cli for Workflow Automation.
Read the repository files that matter first
For this repo, start with SKILL.md because it contains the operational flow and prerequisite details. There are no helper folders to inspect here, so you do not need to spend time searching for rules/, resources/, or scripts/. That makes the reading path unusually short and reduces setup ambiguity.
mcp-cli skill FAQ
Is mcp-cli a replacement for normal MCP integrations?
No. mcp-cli is for on-demand discovery and execution, not for building a permanent integration layer. If your workflow needs always-on server wiring, ordinary integration is a better fit.
Do I need to be an expert to use this skill?
No, but you do need a real server command and a basic understanding of what you want to inspect. Beginners can use it successfully if they can follow a shell command and read the discovered tool list before acting.
When should I not use mcp-cli?
Skip it if you do not have the mcp binary installed, if the server command is unknown, or if you only need a simple one-shot prompt without server inspection. It is also a poor fit when your goal is persistent, production-style orchestration rather than discovery.
What makes mcp-cli different from a generic prompt?
A generic prompt can describe MCP concepts, but mcp-cli is designed around actual command execution: list tools, inspect resources, then choose a call path. That concrete flow reduces guesswork and makes it easier to validate server behavior.
How to Improve mcp-cli skill
Give the skill a precise server target
The best results come from inputs that include the exact server type, launch command, auth needs, and any local paths or environment variables. For example, mcp tools npx -y @modelcontextprotocol/server-filesystem /Users/me/projects is much better than “inspect my files server.”
State the task before the command
Tell the skill whether you are trying to discover capabilities, test a failing server, or automate a specific action. That context changes whether mcp-cli should stop after discovery or continue into resources and prompts.
Watch for common failure modes
Most problems come from missing PATH setup, incomplete server commands, or assuming every server supports tools, resources, and prompts. If output seems sparse, check the server startup command first rather than rewriting the request.
Iterate from discovery to execution
Use the first pass to learn the server surface area, then narrow the request to the exact tool or resource you want next. That two-step loop usually produces better results than asking mcp-cli to solve the whole workflow in one shot.