Mcp2cli

mcp2cli/mcp2skill

Also known as: **mcp2skill** · **mcp-to-cli** · **mcp-to-skill** · **mcpcli** Convert MCP servers into CLI and Agent SKILLs.

Why

For example, install [zereight/gitlab-mcp](https://github.com/zereight/gitlab-mcp) — it exposes **122 tools** across 14 categories (merge requests, issues, pipelines, wikis, etc.). Every tool schema gets injected into your AI conversation context on every request. We measured this directly against the Claude API:

Per-request input tokens	Before (raw MCP)	After (mcp2cli)
Your message	20	20
Tool definitions (122 tools)	27,969	—
Skill file (1 file)	—	~800
Total	27,989	~820
Reduction		~97%

After `mcp2cli convert`, your AI agent stops seeing 122 tool definitions. Instead, it reads one small skill file, and calls CLI commands like `mcp2cli gitlab mr create --project-id 123 --title "Fix bug"` to get the job done.

Beyond token savings, some projects maintain both a CLI and an MCP server in parallel (e.g. the GitLab MCP server vs. the `glab` CLI). Keeping two interfaces in sync is a maintenance burden and inevitably leads to feature drift. mcp2cli eliminates the need — one MCP server, one generated CLI, always consistent.

Quick Start

pip install mcp-to-cli

If you already have an MCP server configured in Claude, Cursor, or Codex:

mcp2cli list              # See which MCP servers are available
mcp2cli convert gitlab-mcp

That's it. Your MCP server is now a CLI, and the compressed skill files are synced to your AI clients.

**Tip:** After install or convert, you can edit `~/.agents/mcp2cli/servers.yaml` to update env vars (API keys, endpoints, etc.) without re-running the full setup.

How It Works

`mcp2cli convert gitlab-mcp` runs a 3-phase pipeline:

┌──────────────┐      ┌──────────────┐