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Mcp Cli

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philschmid
mcp-cli

Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers.

Overview

Publisherphilschmid
Repositorymcp-cli
Skill namemcp-cli
Stars
1.3K
Forks
164
Bundled files
30
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 30 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by philschmid on GitHub. Read the source before you install it.

Installation

Install the Mcp Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/philschmid/mcp-cli.git \
  .claude/skills/mcp-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mcp Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mcp Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mcp Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

MCP-CLI

Access MCP servers through the command line. MCP enables interaction with external systems like GitHub, filesystems, databases, and APIs.

Commands

CommandOutput
mcp-cliList all servers and tools
mcp-cli info <server>Show server tools and parameters
mcp-cli info <server> <tool>Get tool JSON schema
mcp-cli grep "<pattern>"Search tools by name
mcp-cli call <server> <tool>Call tool (reads JSON from stdin if no args)
mcp-cli call <server> <tool> '<json>'Call tool with arguments

Both formats work: <server> <tool> or <server>/<tool>

Workflow

  1. Discover: mcp-cli → see available servers
  2. Explore: mcp-cli info <server> → see tools with parameters
  3. Inspect: mcp-cli info <server> <tool> → get full JSON schema
  4. Execute: mcp-cli call <server> <tool> '<json>' → run with arguments

Examples

bash
# List all servers
mcp-cli

# With descriptions  
mcp-cli -d

# See server tools
mcp-cli info filesystem

# Get tool schema (both formats work)
mcp-cli info filesystem read_file
mcp-cli info filesystem/read_file

# Call tool
mcp-cli call filesystem read_file '{"path": "./README.md"}'

# Pipe from stdin (no '-' needed!)
cat args.json | mcp-cli call filesystem read_file

# Search for tools
mcp-cli grep "*file*"

# Output is raw text (pipe-friendly)
mcp-cli call filesystem read_file '{"path": "./file"}' | head -10

Advanced Chaining

bash
# Chain: search files → read first match
mcp-cli call filesystem search_files '{"path": ".", "pattern": "*.md"}' \
  | head -1 \
  | xargs -I {} mcp-cli call filesystem read_file '{"path": "{}"}'

# Loop: process multiple files
mcp-cli call filesystem list_directory '{"path": "./src"}' \
  | while read f; do mcp-cli call filesystem read_file "{\"path\": \"$f\"}"; done

# Conditional: check before reading
mcp-cli call filesystem list_directory '{"path": "."}' \
  | grep -q "README" \
  && mcp-cli call filesystem read_file '{"path": "./README.md"}'

# Multi-server aggregation
{
  mcp-cli call github search_repositories '{"query": "mcp", "per_page": 3}'
  mcp-cli call filesystem list_directory '{"path": "."}'
}

# Save to file
mcp-cli call github get_file_contents '{"owner": "x", "repo": "y", "path": "z"}' > output.txt

Note: call outputs raw text content directly (no jq needed for text extraction)

Options

FlagPurpose
-dInclude descriptions
-c <path>Specify config file

Common Errors

Wrong CommandErrorFix
mcp-cli server toolAMBIGUOUS_COMMANDUse call server tool or info server tool
mcp-cli run server toolUNKNOWN_SUBCOMMANDUse call instead of run
mcp-cli listUNKNOWN_SUBCOMMANDUse info instead of list
mcp-cli call serverMISSING_ARGUMENTAdd tool name
mcp-cli call server tool {bad}INVALID_JSONUse valid JSON with quotes

Exit Codes

  • 0: Success
  • 1: Client error (bad args, missing config)
  • 2: Server error (tool failed)
  • 3: Network error

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mcp Cli AI skill do?

Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers.

Why use Mcp Cli on TypingMind?

Because you install it once and use it with any model. Mcp Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mcp Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/philschmid/mcp-cli/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mcp Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mcp Cli?

As many as you like. As long as a model supports skills, you can use Mcp Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mcp Cli AI skill free?

Yes. It is published on GitHub by philschmid under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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