heimdall-mcp-server

🥈Silver

Heimdall MCP Server provides long-term memory for AI coding assistants. It benefits developers and operations teams by maintaining context across sessions. It connects to Claude-based agents and integrates with existing development workflows.

97150Updated 1w ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/lcbcFoo/heimdall-mcp-server.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/lcbcFoo/heimdall-mcp-server

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as a coding assistant with long-term memory. Remember that I'm a developer at [COMPANY] working on [PROJECT]. Here's some context about our [INDUSTRY] application: [DATA]. Use this information in all future interactions. First, help me [TASK].

Example Output

# Context Understanding

I've stored the following context about your project:
- Company: TechSolutions Inc.
- Project: Cloud Migration Tool
- Industry: SaaS
- Key Data:
  - Current infrastructure: AWS
  - Target infrastructure: Multi-cloud
  - Key dependencies: Kubernetes, Terraform
  - Team size: 5 developers

# Task Assistance

For your first task, here's how we can approach the cloud migration:
1. **Assessment Phase**:
   - Review current AWS architecture
   - Identify cloud-agnostic components
   - Document potential multi-cloud benefits
2. **Design Phase**:
   - Propose Kubernetes cluster design
   - Suggest Terraform modules for multi-cloud
3. **Implementation Plan**:
   - Phase 1: Lift-and-shift to new cloud
   - Phase 2: Refactor for cloud-agnostic

Would you like to dive deeper into any of these phases?