Mai/.planning/MCP.md

Available Tools & MCP Integration

This document lists all available tools and MCP (Model Context Protocol) servers that Mai development can leverage.

Hugging Face Hub Integration

Status: Authenticated as mystiatech

Tools Available

Model Discovery

• mcp__claude_ai_Hugging_Face__model_search — Search ML models by task, author, library, trending
• mcp__claude_ai_Hugging_Face__hub_repo_details — Get detailed info on any model, dataset, or space

Use Cases:

• Phase 1: Discover quantized models for local inference (Mistral, Llama, etc.)
• Phase 12: Find audio/voice models for visualization
• Phase 13: Find avatar/animation models (VRoid compatible options)
• Phase 14: Research Android-compatible model formats

Dataset Discovery

• mcp__claude_ai_Hugging_Face__dataset_search — Find datasets by task, author, tags, trending
• Search filters: language, size, task categories

Use Cases:

• Phase 4: Training data research for memory compression
• Phase 5: Conversation quality datasets
• Phase 12: Audio visualization datasets

Research Papers

• mcp__claude_ai_Hugging_Face__paper_search — Search ML research papers with abstracts

Use Cases:

• Phase 2: Safety and sandboxing research papers
• Phase 4: Memory system and RAG papers
• Phase 5: Conversational AI and reasoning papers
• Phase 7: Self-improvement and code generation papers

Spaces & Interactive Models

• mcp__claude_ai_Hugging_Face__space_search — Discover Hugging Face Spaces (demos)
• mcp__claude_ai_Hugging_Face__dynamic_space — Run interactive tasks (Image Gen, OCR, TTS, etc.)

Use Cases:

• Phase 12: Voice/audio visualization demos
• Phase 13: Avatar generation or manipulation
• Phase 14: Android UI pattern research

Documentation

• mcp__claude_ai_Hugging_Face__hf_doc_search — Search HF docs and guides
• mcp__claude_ai_Hugging_Face__hf_doc_fetch — Fetch full documentation pages

Use Cases:

• Phase 1: LMStudio/Ollama integration documentation
• Phase 5: Transformers library best practices
• Phase 14: Mobile inference frameworks (ONNX Runtime, TensorFlow Lite)

Account Info

• mcp__claude_ai_Hugging_Face__hf_whoami — Get authenticated user info

Web Research

Tools Available

• WebSearch — Search the web for current information (2026 context)
• WebFetch — Fetch and analyze specific URLs

Use Cases:

• Research current best practices in AI safety (Phase 2)
• Find Android development patterns (Phase 14)
• Discover voice visualization libraries (Phase 12)
• Research avatar systems (Phase 13)
• Find Discord bot best practices (Phase 10)

Code & Repository Tools

Tools Available

• Bash — Execute terminal commands (git, npm, python, etc.)
• Glob — Fast file pattern matching
• Grep — Ripgrep-based content search
• Read — Read file contents
• Edit — Edit files with string replacement
• Write — Create new files

Use Cases:

• All phases: Create and manage project structure
• All phases: Execute tests and build commands
• All phases: Manage git commits and history

Claude Code (GSD) Workflow

Orchestrators Available

• /gsd:new-project — Initialize project
• /gsd:plan-phase N — Create detailed phase plans
• /gsd:execute-phase N — Execute phase with atomic commits
• /gsd:discuss-phase N — Gather phase context
• /gsd:verify-work — User acceptance testing

Specialized Agents

• gsd-project-researcher — Domain research (stack, features, architecture, pitfalls)
• gsd-phase-researcher — Phase-specific research
• gsd-codebase-mapper — Analyze and document existing code
• gsd-planner — Create executable phase plans
• gsd-executor — Execute plans with state management
• gsd-verifier — Verify deliverables match requirements
• gsd-debugger — Systematic debugging with checkpoints

How to Use MCPs in Development

In Phase Planning

When creating /gsd:plan-phase N:

• Researchers can use Hugging Face tools to discover libraries and models
• Use WebSearch for current best practices
• Query papers for architectural patterns

In Phase Execution

When running /gsd:execute-phase N:

• Download models from Hugging Face
• Use WebFetch for documentation
• Run Spaces for prototyping UI patterns

Example Usage by Phase

Phase 1: Model Interface

- mcp__claude_ai_Hugging_Face__model_search
  Query: "quantized models for local inference"
  → Find Mistral, Llama, TinyLlama options
  
- mcp__claude_ai_Hugging_Face__hf_doc_fetch
  → Get Hugging Face Transformers documentation
  
- WebSearch
  → Latest LMStudio/Ollama integration patterns

Phase 2: Safety System

- mcp__claude_ai_Hugging_Face__paper_search
  Query: "code sandboxing, safety verification"
  → Find relevant research papers
  
- WebSearch
  → Docker security best practices

Phase 5: Conversation Engine

- mcp__claude_ai_Hugging_Face__dataset_search
  Query: "conversation quality, multi-turn dialogue"
  
- mcp__claude_ai_Hugging_Face__paper_search
  Query: "conversational AI, context management"

Phase 12: Voice Visualization

- mcp__claude_ai_Hugging_Face__space_search
  Query: "audio visualization, waveform display"
  → Find working demos
  
- mcp__claude_ai_Hugging_Face__model_search
  Query: "speech recognition, audio models"

Phase 13: Desktop Avatar

- mcp__claude_ai_Hugging_Face__space_search
  Query: "avatar generation, VRoid, character animation"
  
- WebSearch
  → VRoid SDK documentation
  → Avatar animation libraries

Phase 14: Android App

- mcp__claude_ai_Hugging_Face__model_search
  Query: "mobile inference, quantized models, ONNX"
  
- WebSearch
  → Kotlin ML Kit documentation
  → TensorFlow Lite best practices

Configuration

Add to .planning/config.json to enable MCP usage:

{
  "mcp": {
    "huggingface": {
      "enabled": true,
      "authenticated_user": "mystiatech",
      "default_result_limit": 10
    },
    "web_search": {
      "enabled": true,
      "domain_restrictions": []
    },
    "code_tools": {
      "enabled": true
    }
  }
}

Research Output Format

When researchers use MCPs, they produce:

• .planning/research/STACK.md — Technologies and libraries
• .planning/research/FEATURES.md — Capabilities and patterns
• .planning/research/ARCHITECTURE.md — System design patterns
• .planning/research/PITFALLS.md — Common mistakes and solutions

These inform phase planning and implementation.

---

Updated: 2026-01-26 Next Review: When new MCP servers become available