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<divalign="center"><b>Run your agents, not your infrastructure.</b></div>
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**mcpd** is a tool to declaratively manage [Model Context Protocol](https://modelcontextprotocol.io/overview) (MCP) servers, providing a consistent interface to define and run tools across environments, from local development to containerized cloud deployments.
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`mcpd` is a tool to declaratively manage [Model Context Protocol](https://modelcontextprotocol.io/overview) (MCP) servers, providing a consistent interface to define and run tools across environments, from local development to containerized cloud deployments.
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Built by [Mozilla AI](https://mozilla.ai)
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📚 [mcpd official docs](https://mozilla-ai.github.io/mcpd/)
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Today, `mcpd` launches MCP servers as subprocesses using STDIO (Standard Input/Output) and acts as an HTTP proxy between agents and the tools they expose. This enables agent-compatible workflows with support for secrets, runtime arguments, and reproducible configurations, no matter where `mcpd` is running.
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`mcpd` solves this with declarative configuration, secure secrets management, and seamless environment promotion - all while keeping the developer experience simple.
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## Why mcpd?
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## Why `mcpd`?
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**Zero-Config Tool Setup**
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No cloning repos or installing language-specific dependencies. `mcpd add` and `mcpd daemon` handle everything.
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**Language-Agnostic Tooling**
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Use MCP servers written in Python, JavaScript, TypeScript via a unified HTTP API.
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Use MCP servers in Docker containers or written in Python, JavaScript, TypeScript via a unified HTTP API.
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**Declarative Configuration**
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Version-controlled `.mcpd.toml` files define your agent infrastructure. Reproducible, auditable, CI-friendly.
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- Smooth dev-to-prod transition via the `mcpd` daemon
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- Rich CLI and SDK tooling, see supported languages below:
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