mcpc – Universal command-line client for Model Context Protocol (MCP)
A universal CLI client for MCP. mcpc supports persistent sessions, stdio/HTTP, OAuth 2.1, tasks, JSON output for code mode, proxy for AI sandboxes, x402, and more. - apify/mcpc
mcpc – Universal command-line client for Model Context Protocol (MCP) launched on January 6, 2026 with 50 votes, #551 of 14,585 launches that month and more than 95% of that year's launches.
In plain words
mcpc is a command-line client that connects to Model Context Protocol (MCP) servers. It enables users to interact with MCP through terminal commands rather than graphical interfaces. The tool is designed for developers and technical users who prefer working in command-line environments and need to access MCP functionality programmatically or through scripts. mcpc provides a universal interface for MCP operations across different systems.
written from the facts on this page · September 2026
Does a similar job
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MCP Server SDK in Bash2025 · github.com · ▲144MCP server SDK/example implemented entirely in bash — build a Model Context Protocol server with no runtime dependency beyond a POSIX shell. - muthuishere/mcp-server-bash-sdk
A MCP server and client implementing the latest spec2025 · github.com · ▲72A comprehensive Model Context Protocol (MCP) server implementing the latest specification. - hemanth/paws-on-mcp

Mcptoon – Token-efficient MCP CLI clientAug 2026 · github.com · ▲73Zero-dep CLI: one MCP config synced to every agent. A 255-tool listing costs 581 tokens, not 71,929 - schemas never enter context. - activeing123/mcptoon
A Model Context Protocol server for NASA APIs2025 · github.com · ▲6A Model Context Protocol (MCP) server for NASA APIs, providing a standardized interface for AI models to interact with NASA's vast array of data sources. - ProgramComputer/NASA-MCP-server
MCP-123, a 2-line MCP server/client (Windows-friendly)2025 · github.com · ▲14Got tired of every MCP example being overly verbose, or needing Docker or Mac-only scripts, so I threw together MCP-123. Point it at a tools.py, run `server.run_server(...)`, and the client auto-discovers/calls functions with OpenAI. I hope this is useful to you all.
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