Skip to content

Mcp2cli

Turn any MCP, OpenAPI, or GraphQL server into a CLI — at runtime, with zero codegen

Install

$npx skills add knowsuchagency/mcp2cli --skill mcp2cli
Claude Code
claude mcp add mcp2cli -- npx skills add knowsuchagency/mcp2cli --skill mcp2cli
Cursor / Claude Desktop (mcp.json)
{
  "mcpServers": {
    "mcp2cli": {
      "command": "npx",
      "args": [
        "skills",
        "add",
        "knowsuchagency/mcp2cli",
        "--skill",
        "mcp2cli"
      ]
    }
  }
}

Install command taken from the project's README or registry entry. Always review code before running it.

mcp2cli

Turn any MCP server, OpenAPI spec, or GraphQL endpoint into a CLI — at runtime, with zero codegen. Save 96–99% of the tokens wasted on tool schemas every turn. Read the full writeup →

Install

# Run directly without installing
uvx mcp2cli --help

# Or install globally
uv tool install mcp2cli

AI Agent Skill

mcp2cli ships with an installable skill that teaches AI coding agents (Claude Code, Cursor, Codex) how to use it. Once installed, your agent can discover and call any MCP server or OpenAPI endpoint — and even generate new skills from APIs.

npx skills add knowsuchagency/mcp2cli --skill mcp2cli

After installing, try prompts like:

  • mcp2cli --mcp https://mcp.example.com/sse — interact with an MCP server
  • mcp2cli create a skill for https://api.example.com/openapi.json — generate a skill from an API

Usage

MCP HTTP/SSE mode

# Connect to an MCP server over HTTP
mcp2cli --mcp https://mcp.example.com/sse --list

# Call a tool
mcp2cli --mcp https://mcp.example.com/sse search --query "test"

# With auth header
mcp2cli --mcp https://mcp.example.com/sse --auth-header "x-api-key:sk-..." \
  query --sql "SELECT 1"

# Force a specific transport (skip streamable HTTP fallback dance)
mcp2cli --mcp https://mcp.example.com/sse --transport sse --list

# Search tools by name or description (case-insensitive substring match)
mcp2cli --mcp https://mcp.example.com/sse --search "task"

--search implies --list and works across all modes (--mcp, --spec, --graphql, --mcp-stdio).

OAuth authentication

APIs that require OAuth are supported out of the box — across MCP, OpenAPI, and GraphQL modes. mcp2cli handles token acquisition, caching, and refresh automatically.

# Authorization code + PKCE flow (opens browser for login)
mcp2cli --mcp https://mcp.example.com/sse --oauth --list
mcp2cli --spec https://api.example.com/openapi.json --oauth --list
mcp2cli --graphql https://api.example.com/graphql --oauth --list

# Client credentials flow (machine-to-machine, no browser)
mcp2cli --spec https://api.example.com/openapi.json \
  --oauth-client-id "my-client-id" \
  --oauth-client-secret "my-secret" \
  list-pets

# With specific scopes
mcp2cli --graphql https://api.example.com/graphql --oauth --oauth-scope "read write" users

# Local spec file — use --base-url for OAuth discovery
mcp2cli --spec ./openapi.json --base-url https://api.example.com --oauth --list

Tokens are persisted in ~/.cache/mcp2cli/oauth/ so subsequent calls reuse existing tokens and refresh automatically when they expire.

Headless hosts — no browser on the machine running mcp2cli

The default authorization-code flow starts a callback server on 127.0.0.1, which only works when the browser runs on the same machine. On a VPS over SSH or in a container, add --oauth-manual-callback: mcp2cli prints the authorization URL instead of opening a browser, and reads the redirect back from stdin.

mcp2cli --mcp https://mcp.linear.app/mcp --oauth --oauth-manual-callback --list

Open the printed URL in a browser on any machine, authorize, then paste the URL you land on. That page will fail to load — nothing is listening on the loopback port — which is expected; only its address matters, because it carries the code and state parameters. PKCE and state verification are unchanged, so paste the URL unmodified.

Similar plugs

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

Java 面试 & 后端通用面试指南,覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发

Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype…