MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Mcp-Cli

Mcp-Cli是一款data方向的AI技能,核心价值是Interface for MCP (Model Context Protocol) servers via CLI,可用于解决开发者在data领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

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, list available MCP servers/tools, or call MCP

Last verified on: 2026-05-30
mkdir -p ./skills/mcp-cli && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/mcp-cli/SKILL.md -o ./skills/mcp-cli/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# MCP-CLI


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


Commands


| Command | Output |

| ---------------------------------- | ------------------------------- |

| `mcp-cli` | List all servers and tool names |

| `mcp-cli <server>` | Show tools with parameters |

| `mcp-cli <server>/<tool>` | Get tool JSON schema |

| `mcp-cli <server>/<tool> '<json>'` | Call tool with arguments |

| `mcp-cli grep "<glob>"` | Search tools by name |


**Add `-d` to include descriptions** (e.g., `mcp-cli filesystem -d`)


Workflow


1. **Discover**: `mcp-cli` → see available servers and tools

2. **Explore**: `mcp-cli <server>` → see tools with parameters

3. **Inspect**: `mcp-cli <server>/<tool>` → get full JSON input schema

4. **Execute**: `mcp-cli <server>/<tool> '<json>'` → run with arguments


Examples


bash
# List all servers and tool names
mcp-cli

# See all tools with parameters
mcp-cli filesystem

# With descriptions (more verbose)
mcp-cli filesystem -d

# Get JSON schema for specific tool
mcp-cli filesystem/read_file

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

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

# JSON output for parsing
mcp-cli filesystem/read_file '{"path": "./README.md"}' --json

# Complex JSON with quotes (use heredoc or stdin)
mcp-cli server/tool <<EOF
{"content": "Text with 'quotes' inside"}
EOF

# Or pipe from a file/command
cat args.json | mcp-cli server/tool

# Find all TypeScript files and read the first one
mcp-cli filesystem/search_files '{"path": "src/", "pattern": "*.ts"}' --json | jq -r '.content[0].text' | head -1 | xargs -I {} sh -c 'mcp-cli filesystem/read_file "{\"path\": \"{}\"}"'

Options


| Flag | Purpose |

| ------------ | ------------------------- |

| `-j, --json` | JSON output for scripting |

| `-r, --raw` | Raw text content |

| `-d` | Include descriptions |


Exit Codes


- `0`: Success

- `1`: Client error (bad args, missing config)

- `2`: Server error (tool failed)

- `3`: Network error

🎯 Best For

  • Claude users
  • GitHub Copilot users
  • Data professionals
  • Analytics teams
  • Researchers

💡 Use Cases

  • Data pipeline auditing
  • Query optimization

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Mcp-Cli to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install Mcp-Cli?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/mcp-cli/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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