Process Compose – I added embedded MCP server to process-compose
Zero-code MCP exposure for existing CLI commands, but MCP adoption is still niche.
Turn MCP servers into composable CLIs.
MCP servers as shell pipes—clever abstraction, but only matters if you're already in the MCP ecosystem.
Agent developers (OpenClaw, Claude Code), CLI tool builders, and engineers integrating MCP servers into shell-first workflows.
ModelContextProtocol (MCP itself) · Claude Code native tool integration
Core idea: MCPX turns MCP servers into Unix-composable commands for agent workflows. It is primarily for agents that are shell-first, and secondarily useful for humans running tools directly.
For me, a practical use case is OpenClaw: OpenClaw can call `mcpx` like any normal CLI and use MCP servers immediately, without implementing custom MCP transport/auth plumbing in OpenClaw itself. This also fits well with Codex Apps mode, where connected apps can be exposed as MCP servers through the same command contract.
Command contract: - mcpx - mcpx <server> - mcpx <server> <tool>
Design choices: - schema-aware `--help` (inputs + declared outputs) - native flag surface from MCP `inputSchema` - pass-through tool output for normal shell composition (`jq`, `head`, pipes) - explicit exit mapping (`0/1/2/3`) - stdio + HTTP server support - optional caching - `mcpx add` for bootstrapping server config from install links/manifests/endpoints
Examples: - mcpx github search-repositories --help - mcpx github search-repositories --query=mcp - echo '{"query":"mcp"}' | mcpx github search-repositories
Install: - brew tap lydakis/mcpx && brew install --cask mcpx - npm i -g mcpx-go - pip install mcpx-go
I would love feedback on command UX, schema/flag edge cases, and where this should stop vs expand.
Zero-code MCP exposure for existing CLI commands, but MCP adoption is still niche.
Cuts AI agent token costs 80% by wrapping MCP servers as native shell commands.
The project implements a sandboxed, server-side 'shell' that pipes MCP tool calls together so agents return only final outputs — a smart way to save tokens and handle datasets too large for LLM context. The repo includes a demo video, tests, and a real shell_engine/mcp_client implementation, but it's a focused infra play for the MCP ecosystem and will matter most to teams building agent platforms rather than general devs.
Reverse-engineered proprietary protocols let AI compose directly on hardware synth.
Identity-based permissioning changes AI capabilities per active persona stack.
Apple Intelligence integration means free inference on MacBooks without API keys.