mcp-cli

$npx mdskill add github/awesome-copilot/mcp-cli

Interact with external systems, APIs, and data sources by calling defined tools via the command line.

  • Enables programmatic interaction with external services like databases or file systems.
  • Integrates with any service exposed via the Model Context Protocol (MCP).
  • Determines necessary calls by allowing discovery, schema inspection, and direct execution.
  • Delivers results through structured command-line output, including JSON schemas.

SKILL.md

.github/skills/mcp-cliView on GitHub ↗
---
name: mcp-cli
description: 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 tools from command line.
---

# 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

More from github/awesome-copilot

SkillDescription
acquire-codebase-knowledgeUse this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
acreadiness-assessRun the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
acreadiness-generate-instructionsGenerate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
acreadiness-policyHelp the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
add-educational-comments'Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.'
adobe-illustrator-scriptingWrite, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
agent-governance|
agent-owasp-compliance|
agent-supply-chain|
agentic-eval|