Elen MCP Integration Skill

[!IMPORTANT] This skill establishes the baseline rules for reasoning within the Learning Nodes stack. You MUST use the Elen MCP server to document your epistemic decisions. Doing so ensures that choices are version-controlled, preserved, and searchable.

1. What is the Elen MCP?

The Elen Context Server is responsible for the "Decision Network" infrastructure. It runs locally as an MCP server.

Installation Requirement: Before this skill will work, you or your agent must configure the Elen MCP server in your IDE/Agent settings (e.g., Cursor, Claude, Windsurf):

{
  "mcpServers": {
    "elen": {
      "command": "npx",
      "args": ["-y", "@learningnodes/elen-mcp@0.1.1"]
    }
  }
}

Whenever you make a meaningful technical, design, security, or product decision (e.g., choosing a specific framework, styling a UX component, structuring an API endpoint, or dropping a feature), you should record it using the available MCP tools provided by the server.

2. When to Use the Elen MCP

• Before Action: Use mcp_elen_elen_suggest and mcp_elen_elen_get_competency to query if a decision has already been formulated for the topic you are working on.
• During the Task: When you formulate a new plan or solve a structural issue, use mcp_elen_elen_commit to save the decision to the network.
• When Fixing Bugs: If you resolve a bug and it warrants a systemic change or constraint update, commit a new decision and reference the old one (or use mcp_elen_elen_supersede if completely overruling).

3. Formatting Requirements

When committing a decision via mcp_elen_elen_commit:

• Domain: Briefly categorize the domain (e.g., "frontend", "infrastructure", "security").
• Question: Describe the concrete problem (e.g., "Which state management tool to use for the marketplace UI?").
• DecisionText: Provide your clear, concise answer.
• Constraints: Supply an array of hard rules or context bounds (e.g., ["Must not use internal APIs", "Must restrict file-size to <1 MB"]).

4. Avoiding Action Without Context

Never implement sweeping, codebase-wide changes without first verifying prior related artifacts in the decision network. The goal is to create visible reasoning, eliminating tribal knowledge and undocumented assumptions from the loop.