The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Mcpc
The most compatible MCP CLI client. Supports: tools, resources, prompts, completions, async tasks, skills, stdio and Streamable HTTP (MCP 2026-07-28 and 2025-11-25). Persistent…
Install
npm install -g @apify/mcpcInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →mcpc — a universal MCP CLI client
mcpc is a command-line client for the Model Context Protocol (MCP)
that maps every MCP operation to an intuitive shell command.
Use it to manually inspect and debug MCP servers, to script repeatable MCP workflows in plain shell, or to
give AI agents the full MCP protocol through a single Bash() tool call, so they can interact with any MCP
server and its latest capabilities using the most universal programming interface there is: the UNIX shell.
Key features:
- 🔧 Full MCP support - Tools, prompts, resources, async tasks, skills, notifications, and logging over stdio and Streamable HTTP.
- 🔄 Persistent sessions - Keep connections to multiple servers alive in parallel, whether the server protocol is stateful or stateless.
- 🗺️ Progressive tool discovery - Find relevant MCP tools on the fly to save tokens and increase accuracy.
- 🔌 Code mode - JSON output composes with
jq,xargs, and shell pipelines for MCP workflows as shell scripts. - 🔒 Secure - Full OAuth 2.1 support with CIMD and DCR, uses OS keychain for credentials storage.
- 🤖 AI sandboxing - Proxy MCP server connections to protect credentials from AI-generated code.
- 🪶 Lightweight - Minimal dependencies, works on Mac/Win/Linux, doesn't use LLMs on its own.
- 💸 Agentic payments - Experimental support for the x402 protocol on Base.
mcpc is the most MCP specification-compliant CLI client available:
the only one that covers tools, resources, prompts, async tasks, and skills, plus the OAuth client-credentials and
enterprise-managed authorization extensions, on the latest protocol version. Here's how it compares to other MCP CLI
clients (see Related work for the full table, legend, and notes):
Table of contents
- Motivation
- Install
- Quickstart
- Usage
- Sessions
- Authentication
- MCP proxy
- AI agents
- Agentic payments (x402)
- MCP support
- Configuration
- Security
- Errors
- Development
- Related work
- License
Motivation
Many AI agents misuse MCP. They treat tools as prompt-time function calls, repeatedly injecting tool definitions and results into the context. Tokens get wasted, context rots, the agent gets slower and less reliable — hence the popular conclusion: "MCP sucks, CLIs are better".
mcpc challenges that narrative. It maps every MCP operation to an intuitive CLI command that
agents pick up from --help alone. Any agent with shell access gets full MCP support without
wiring up dozens of MCP functions. Just one Bash() tool, and mcpc handles the rest:
┌──────────┐ Bash() ┌────────┐ MCP ┌────────────┐
│ AI agent │ ─────────► │ mcpc │ ────────► │ MCP server │
└──────────┘ └────────┘ └────────────┘
Sessions, OAuth, Tools,
Resources, Prompts,
Tasks, Skills, x402, ...
Similar plugs
Reverse engineer anything with agents, from app behavior down to native binaries.
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…
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.