Summary
A prompt management server that exposes CRUD operations for LLM prompts through MCP tools like add_prompt, get_prompt, and apply_template. It handles template variable substitution, supports multiple storage backends including DynamoDB and S3, and can run in stdio mode for Claude Desktop or HTTP mode for REST integrations. The cognitive architecture layers add context-aware prompt recommendations and cross-domain pattern matching. You'd reach for this when building applications that need centralized prompt storage, versioning, and intelligent template management across different AI workflows, especially if you're already using AWS infrastructure or need Stripe payment integration for prompt marketplace features.
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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
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Download Free life-time →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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