Llun MCP server
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# Llun-MCP - Architectural Context for Agents ## Intro Llun-MCP extends [Llun](https://pypi.org/project/llun/) into the world of agentic workflows through the [Model Context Protocol](https://modelcontextprotocol.io/docs/getting-started/intro) (MCP). While the Llun CLI tool helps developers enforce architectural principles during coding, Llun-MCP gives agents the same advantage — ensuring they design and generate solutions that align with **your** architectural rules from the very beginning. Rather than waiting until code is complete to lint and fix, Llun-MCP injects your team’s architectural principles directly into the agent’s reasoning loop. This prevents the kind of ad-hoc, inconsistent output that often plagues LLM-driven code generation, and minimises the need for post agent clean-up. To achieve this, Llun-MCP exposes a single, simple tool: `get_rules` - which provides the agents with the user selected architectural rules defined by their chosen config tomls. Through encouraging agents to utilise this tool prior to beginning coding tasks, Llun-MCP ensures all agentic workflows begin with a complete understanding of the underlying principles the solution should adhere to. By utilising STDIO, Llun-MCP remains fully portable to all agentic workflows regardless of networking setups, choice of LLM, etc... All of this makes Llun-MCP perfect for teams that want to: - Use agents as coding assistants without sacrificing design consistency - reduce cost of agentic coding activities by ensuring the first results produced are close to the teams agreed standards - Utilise Llun CLI for architectural assessment - ensure agent-powered high velocity development doesnt come with a sacrifice in maintainability ## Quick Start ### Installation to use the server, the fastest way is to pip install it into a local environment: ``` uv pip install llun-mcp ``` or for those not yet ready to migrate to uv: ``` pip install llun-mcp ``` ### Basic Usage To use the tool in CLa…
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