# MCP ECOSYSTEM STRATEGY
## INITIATIVE-020 — Phase 4
**Project:** Skills Tree · **Date:** 2026-06-24

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## Overview

The Model Context Protocol (MCP) is the emerging standard for connecting AI assistants to external data and tools. Skills Tree, as a structured knowledge graph of AI engineering capabilities, is a natural first-class MCP server. This document defines the strategy for becoming the default skills intelligence layer across the MCP ecosystem.

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## Strategic Position

Skills Tree MCP = "the skills OS that AI assistants call when they need to reason about AI engineering."

When a developer asks Cursor: *"What skills do I need to build a memory-enabled agent?"* — the answer should come from Skills Tree, not from the model's stale training data.

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## Target Integrations

### Tier 1 — Immediate (Q3 2026)

| Platform | Integration Method | Outcome |
|----------|--------------------|--------|
| **Claude (Anthropic)** | claude.ai MCP marketplace listing | Accessible to all Claude Pro/Teams users |
| **Cursor** | Cursor MCP registry | Available inside every Cursor IDE session |
| **Windsurf (Codeium)** | Windsurf plugin marketplace | Available to Windsurf's developer base |
| **VS Code Copilot** | MCP extension manifest | Available via VS Code extensions |

### Tier 2 — Medium Term (Q4 2026)

| Platform | Integration Method | Outcome |
|----------|--------------------|--------|
| **OpenAI Agents SDK** | Tool registration via MCP adapter | Agents can query skills graph as a tool |
| **CrewAI** | Custom tool wrapper | CrewAI agents use skills graph for role design |
| **LangGraph** | LangGraph tool node | Graph-aware agent pipelines |
| **AutoGen** | Tool registration | AutoGen agents query skill dependencies |

### Tier 3 — Strategic (H1 2027)

| Platform | Integration Method | Outcome |
|----------|--------------------|--------|
| **GitHub Copilot** | MCP extension | Skills graph accessible in GitHub Copilot chat |
| **Replit AI** | Plugin integration | Available to Replit's large learner community |
| **AWS Bedrock Agents** | Knowledge base connector | Enterprise-grade integration |

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## MCP Server Capabilities (V1 Spec)

The Skills Tree MCP server exposes the following tools:

```
TOOL: get_skill
  Input:  { skill_name: string }
  Output: { id, name, category, description, dependencies, related_skills, difficulty }

TOOL: search_skills
  Input:  { query: string, category?: string, limit?: number }
  Output: { skills: Skill[], total_matches: number }

TOOL: get_skill_stack
  Input:  { goal: string }
  Output: { required_skills: Skill[], optional_skills: Skill[], learning_order: string[] }

TOOL: get_blueprint
  Input:  { agent_type: string }
  Output: { blueprint: Blueprint, skill_stack: Skill[], dependencies: string[] }

TOOL: get_learning_path
  Input:  { target_role: string, current_skills?: string[] }
  Output: { phases: LearningPhase[], estimated_weeks: number }

TOOL: get_skill_dependencies
  Input:  { skill_id: string, depth?: number }
  Output: { dependency_tree: SkillNode, all_dependencies: string[] }
```

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## Distribution Strategy

### Step 1 — Marketplace Listings (Week 1–2)

Submit MCP server to:
- Anthropic's MCP server registry (modelcontextprotocol.io)
- Cursor's plugin marketplace
- Awesome-MCP-Servers GitHub list (high-traffic community index)
- Windsurf plugin directory

Each listing requires: server name, description, tool list, installation command, and a demo GIF.

### Step 2 — Launch Content (Week 3)

Publish:
- Blog post: "Query the AI skills graph from inside Cursor" (with demo video)
- GitHub README updated with one-click MCP install badge
- Short demo thread on X/Twitter showing Claude answering "what skills for RAG?" using Skills Tree

### Step 3 — Integration Partnerships (Month 2–3)

Reach out to:
- CrewAI team (open-source, community-driven, receptive to integrations)
- LangGraph team (actively building ecosystem)
- AutoGen team (Microsoft-backed, enterprise reach)

Offer: co-authored blog post + integration example in their docs.

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## Versioning & Reliability Contract

MCP consumers need a stable contract. Skills Tree MCP must commit to:

- Semantic versioning on graph schema (breaking changes require major version bump)
- Changelog feed (RSS or GitHub Releases) that MCP consumers can subscribe to
- 99.9% uptime for hosted MCP endpoint (Vercel Edge Functions, global CDN)
- Zero-downtime graph updates (atomic JSON replacement, not incremental patching)

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## Competitive Moat via MCP

Once Skills Tree is embedded in Claude, Cursor, and Windsurf — it becomes the **default reference** for AI engineering skills. Users stop searching Google and start querying the graph. Every new skill added to the graph increases the value of every existing integration. This is a compounding moat: early presence in MCP marketplaces creates a first-mover advantage that is difficult to displace once developer habits form.
