oh-mcp

Open Horizons MCP Server

Model Context Protocol (MCP) server for Open Horizons - enables AI agents to read and write strategic alignment context.

What is This?

Open Horizons MCP Server connects AI coding assistants (like Claude Code) to your strategic alignment framework. Instead of making isolated technical decisions, AI agents can:

• Read your strategic context: Query missions, aims, initiatives, and tasks
• Log decisions back: Document why choices were made, tied to strategic goals
• Stay aligned: Every code change traces back to a mission

The result: AI that doesn't just code fast—it codes in alignment with your strategy.

Quick Start

1. Get Your API Key

1. Sign up at app.openhorizons.me
2. Go to Settings > API Keys
3. Create a new API key

2. Choose Your Setup Method

Option A: Plugin Setup (Recommended for Claude Code)

The plugin provides a guided /oh-mcp:setup command:

# Add the marketplace
claude plugin marketplace add cloud-atlas-ai/oh-mcp-server

# Install the plugin
claude plugin install oh-mcp@oh-mcp

# Restart Claude Code, then run:
/oh-mcp:setup

Option B: Direct CLI Setup (No Plugin Needed)

Use the claude mcp add command directly:

claude mcp add oh-mcp -s user \
  -e OH_API_URL=https://app.openhorizons.me \
  -e OH_API_KEY=your_api_key_here \
  -- npx -y @cloud-atlas-ai/oh-mcp-server

This adds the MCP server to ~/.claude.json so it's available in all projects.

Option C: Project-Specific Setup

Add to your project's .mcp.json:

{
  "mcpServers": {
    "oh-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cloud-atlas-ai/oh-mcp-server"],
      "env": {
        "OH_API_KEY": "your_api_key_here",
        "OH_API_URL": "https://app.openhorizons.me"
      }
    }
  }
}

3. Verify

Restart Claude Code, then ask Claude to test the connection:

Try calling: oh_about

If it works, you'll see OH MCP tools available!

Available Tools

Read Operations

• oh_get_contexts - List all contexts (personal and shared workspaces)
• oh_get_endeavors - Get endeavors (missions, aims, initiatives, tasks) in a context
• oh_get_endeavor - Get details of a specific endeavor with hierarchy
• oh_get_logs - Get recent logs/decisions for an endeavor
• oh_about - Get information about Open Horizons and this MCP server

Write Operations (Endeavors)

• oh_create_endeavor - Create new mission, aim, initiative, or task
• oh_update_endeavor - Update endeavor title and/or description
• oh_archive_endeavor - Archive endeavor (soft delete)
• oh_unarchive_endeavor - Restore an archived endeavor
• oh_set_parent - Change parent of an endeavor (move in hierarchy)
• oh_delete_endeavor - Permanently delete an endeavor

Write Operations (Logging & Learning)

• oh_log_decision - Log decision, note, or progress to an endeavor
• oh_update_log - Update a log entry's content
• oh_delete_log - Delete a log entry
• oh_create_metis_candidate - Surface a pattern/learning for later review (metis = situated judgment)
• oh_create_guardrail_candidate - Surface a constraint/rule that should be enforced

Write Operations (Candidates)

• oh_create_metis_candidate - Surface a pattern/learning for later review
• oh_create_guardrail_candidate - Surface a constraint/rule for later review

Write Operations (Contexts)

• oh_create_context - Create new shared context (workspace)
• oh_update_context - Update context title and/or description
• oh_move_endeavor - Move endeavor to different context
• oh_delete_context - Permanently delete a context
• oh_invite_to_context - Invite user by email with role (editor or viewer)

Core Concepts

Open Horizons uses a four-level alignment hierarchy:

Mission (why you exist)
  └── Aim (outcome you want)
       └── Initiative (how you'll achieve it)
            └── Task (what you do today)

Key Ideas:

• Contexts: Personal or shared spaces where endeavors live
• Endeavors: Any node in the hierarchy (mission, aim, initiative, task)
• Decision logs: Captured reasoning and progress tied to endeavors
• Alignment: Every task traces back to a mission, so you always know why
• Metis: Situated judgment - patterns and learnings captured from real work
• Guardrails: Executable constraints that prevent repeating mistakes

Learning Capture Workflow

When agents discover a reusable insight or constraint during work: