Simple MCP server for managing AI prompts and agent configurations with direct claude CLI orchestration.
개요
Simple MCP server for managing AI prompts and agent configurations with direct claude CLI orchestration.
README
mcp-prompts
Simple MCP server for managing AI prompts and agent configurations with direct claude CLI orchestration.
What It Does
- Stores prompts as JSON files in
data/prompts/ - Exposes MCP tools for querying and managing prompts
- Provides agent templates for project orchestration
- Works with Claude Desktop, Cursor, and other MCP clients
Quick Start
1. Install
pnpm install
pnpm build
2. Start MCP Server
pnpm start
3. Configure Claude Desktop
Add to ~/.claude/mcp.json:
{
"mcpServers": {
"prompts": {
"command": "node",
"args": ["/absolute/path/to/mcp-prompts/dist/mcp-server-standalone.js"],
"env": {
"PROMPTS_DIR": "/absolute/path/to/mcp-prompts/data/prompts"
}
}
}
}
4. Use in Claude
Ask Claude:
- “List all prompts tagged with esp32”
- “Get the esp32-fft-configuration-guide prompt”
- “Create a new prompt for Python FastAPI best practices”
Orchestrating Projects
Use the orchestrate script to analyze entire projects:
./scripts/orchestrate-project.sh ~/projects/mia analyze
./scripts/orchestrate-project.sh ~/projects/esp32-bpm-detector review
This automatically:
- Detects project type
- Loads appropriate main agent
- Spawns specialized subagents
- Runs comprehensive analysis
- Returns structured results
MCP Tools
| Tool | Description |
|---|---|
list_prompts |
Query prompts with filters (tags, search, category) |
get_prompt |
Retrieve specific prompt with template expansion |
create_prompt |
Add new prompt to repository |
update_prompt |
Modify existing prompt |
delete_prompt |
Remove prompt |
apply_template |
Apply variables to template string |
get_stats |
Repository statistics |
Prompts Organization
data/prompts/
├── main-agents/ # 7 project orchestration templates
│ ├── main_agent_python_backend.json
│ ├── main_agent_cpp_backend.json
│ ├── main_agent_android_app.json
│ ├── main_agent_embedded_iot.json
│ ├── main_agent_multiplatform_iot.json
│ └── ...
│
├── subagents/ # 19 specialized analysis agents
│ ├── explorer.json # Project discovery
│ ├── analyzer.json # Code analysis
│ ├── diagrammer.json # Diagram generation
│ ├── solid_analyzer.json # Code quality
│ └── ...
│
├── cognitive/ # 7-layer cognitive architecture
├── esp32/ # Embedded systems patterns
├── mcp-tools/ # MCP usage patterns
└── [domains]/ # Domain-specific knowledge
Architecture
Simple and focused:
┌──────────────────────────────┐
│ MCP Server (stdio) │
│ ├── list_prompts │
│ ├── get_prompt │
│ ├── create_prompt │
│ └── ... │
├──────────────────────────────┤
│ File Storage │
│ └── data/prompts/*.json │
└──────────────────────────────┘
Orchestration:
orchestrate-project.sh
↓ loads prompts
↓ builds agent config
↓ calls claude CLI
Actual agent execution
Development
pnpm install # Install dependencies
pnpm build # Build TypeScript
pnpm dev # Watch mode
pnpm test # Run tests
pnpm orchestrate # Test orchestration
Enterprise Deployment
For enterprise features (AWS, multi-tenant, payments), see archive/aws/README.md.
Most users don’t need this - the local MCP server is sufficient.
License
MIT
설치
This server does not publish a one-line install command.
Open the repository installation guide설정
{
"mcpServers": {
"prompts": {
"command": "node",
"args": ["/absolute/path/to/mcp-prompts/dist/mcp-server-standalone.js"],
"env": {
"PROMPTS_DIR": "/absolute/path/to/mcp-prompts/data/prompts"
}
}
}
}