Use the command line to discover and run tools on MCP servers, which connect agents to external systems. Inspect required inputs, pass JSON arguments, and retrieve results as JSON or raw text for scripts.
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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.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Access MCP servers through the command line. MCP enables interaction with external systems like GitHub, filesystems, databases, and APIs.
| 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)
mcp-cli → see available servers and toolsmcp-cli <server> → see tools with parametersmcp-cli <server>/<tool> → get full JSON input schemamcp-cli <server>/<tool> '<json>' → run with arguments# 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\": \"{}\"}"'
| Flag | Purpose |
|---|---|
-j, --json | JSON output for scripting |
-r, --raw | Raw text content |
-d | Include descriptions |
0: Success1: Client error (bad args, missing config)2: Server error (tool failed)3: Network error아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
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