[](https://mseep.ai/app/stevengonsalvez-promptregistry-mcp)
# Prompt Registry: Your Personal Prompt Registry Server 🏰✍️
[](https://smithery.ai/server/@stevengonsalvez/promptregistry-mcp)
**MCP Prompt Registry** is a lightweight, file-based [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) prompt server designed for developers. It runs via `stdio`, making it perfect for local development and integration with CLIs or desktop AI assistants that support MCP. It allows you to manage your prompts in a single directory, keeping your workflow simple and portable.
## ✨ Features
* **Single Prompt Storage Directory:**
* All prompts are stored in a single directory. You can control the location with the `PROMPT_REGISTRY_PROJECT_DIR` environment variable. If not set, prompts are stored in `~/.promptregistry/` in your home directory.
* **File-Based:** Prompts are simple JSON files – easy to read, edit, and version control.
* **Standard MCP Compliance:**
* Exposes prompts via standard `prompts/list` (lists all prompts).
* Allows prompts to be used via standard `prompts/get` (applies template variables).
* Notifies clients of changes via `notifications/prompts/list_changed`.
* **Management via MCP Tools:**
* `add_prompt`: Add new prompts.
* `get_prompt_file_content`: View the raw JSON of a prompt.
* `update_prompt`: Modify prompts.
* `delete_prompt`: Remove prompts.
* `filter_prompts_by_tags`: Discover prompts by tags.
* **Stdio Interface:** Communicates over standard input/output, ideal for local tools.
* **Template Variables:** Supports `{{variable_name}}` syntax in prompt content.
* **Zod Schema Validation:** Robust validation for tool arguments.
## Prerequisites
* **Node.js:** Version 18 or higher.
* **npm** (or **yarn**).
* **(Optional) Docker:** If you want to run the server in a container.
## 📁 Directory Structure for Prompts
The server uses a single directory for all prompts:
1. If the environment variable `PROMPT_REGISTRY_PROJECT_DIR` is set, prompts are stored in that directory.
2. If not set, prompts are stored in `~/.promptregistry/` in your home directory. On first startup, or if prompts are missing, the server will attempt to copy predefined prompts from a local `default_prompts_data/` directory (if present) into `~/.promptregistry/`.
**Prompt JSON File Structure (`your-prompt-id.json`):**
```json
{
"id": "your-prompt-id",
"description": "A brief description for MCP listing",
"content": "Your prompt template, e.g., Explain {{concept}} like I'm {{age}}.",
"tags": ["tag1", "category_a"],
"variables": {
"concept": { "description": "The concept to explain", "required": true },
"age": { "description": "The target audience's age", "required": false }
},
"metadata": { "version": "1.1", "author": "You" }
}
```
## 🚀 Installation and Running
### Installing via Smithery
To install Prompt Registry for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@stevengonsalvez/promptregistry-mcp):
```bash
npx -y @smithery/cli install @stevengonsalvez/promptregistry-mcp --client claude
```
### 1. Using the Published NPM Package (Recommended for Clients)
If `promptregistry-mcp` is published to npm, clients can easily run it.
1. **Ensure Node.js and npx are installed.**
2. Configure your MCP client (like Claude Desktop or Amazon Q) to use it. See examples below.
### 2. Local/Manual Installation (For Development or Direct Use)
1. **Clone the repository or download the files:**
(Assuming you have `server.ts`, `package.json`, `tsconfig.json`, and an optional `default_prompts_data/` directory)
2. **Install dependencies:**
Navigate to the server's root directory in your terminal:
```bash
npm install
# or
# yarn install
```
3. **Build the server (compile TypeScript):**
```bash
npm run build
```
This will create a `dist/` directory with the compiled JavaScript.
4. **Run the server:**
* For development (uses `tsx` to run TypeScript directly, with auto-restart on changes):
```bash
npm run dev
```
* To run the compiled version:
```bash
npm run start:prod
```
The server will start listening on `stdin` and outputting to `stdout`.
Console messages from the server (like "Server is running...") will appear on `stderr`.
It will create the prompt directory (either as specified by `PROMPT_REGISTRY_PROJECT_DIR` or `~/.promptregistry/`) if it doesn't exist.
### 3. Running with Docker
1. **Build the Docker image:**
Ensure you have Docker installed. From the server's root directory:
```bash
docker build -t mcp-promptregistry .
```
*(You can change `mcp-promptregistry` to `promptregistry-mcp` or your preferred image name)*
2. **Run the Docker container:**
```bash
docker run -i -t --rm mcp-promptregistry
```
* `-i`: Keep STDIN open (interactive).
The container will have its own internal prompt directory. To persist prompts outside the container or use existing local prompts:
```bash
# Example: Mount local directory into the container
docker run -i -t --rm \
-v "$HOME/.promptregistry:/root/.promptregistry" \
mcp-promptregistry
```
*(Note: The home directory for the `root` user inside the Alpine container is `/root`)*
## 🔌 Connecting with MCP Clients
Here's how you might configure clients like Claude Desktop or Amazon Q to use your MCP Prompt Registry. The exact JSON structure might vary slightly based on the client's implementation, but the core idea is to define a stdio server.
**Option A: Using the (Hypothetically) Published NPM Package `promptregistry-mcp`**
If this server were published to npm as `promptregistry-mcp`, the configuration would be very clean:
```json
// Example client configuration JSON
{
"mcpServers": {
"mcp-promptregistry": {
"command": "npx",
"args": [
"mcp-promptregistry"
],
"env": {
"PROMPT_REGISTRY_PROJECT_DIR": "/path/to/your/prompts"
}
}
}
}
```
*This assumes `promptregistry-mcp` when run via `npx` correctly starts the stdio server.*
**Option B: Running from Local (Compiled) Source**
If you've built the server locally and want to point your client to it:
```json
// Example client configuration JSON
{
"mcpServers": {
"localPromptRegistry": {
"command": "node",
"args": [
"/full/path/to/your/mcp-promptregistry/dist/server.js"
],
"env": {}
}
}
}
```
*Replace `/full/path/to/your/mcp-promptregistry/` with the actual absolute path to where you cloned/built the server.*
**Important Considerations for Client Configuration:**
* **Absolute Paths:** When specifying paths for local commands (Option B), always use absolute paths, as the client application might execute the command from a different working directory.
* **Environment Variables (`env`):** Use `PROMPT_REGISTRY_PROJECT_DIR` to control where prompts are stored.
* **Client-Specific Structure:** The top-level key (e.g., `"mcpServers"`) and the exact structure can vary between different MCP client applications. Adapt the `command`, `args`, and `env` to fit the client's requirements. The key is how it invokes your stdio server.
## 🧪 Testing the Server
### 1. Manual Stdio (JSON-RPC)
The most direct way to test. Run your server, then paste JSON-RPC messages into the same terminal and press Enter.
*Example `prompts/list` request:*
```json
{"jsonrpc":"2.0","id":"list1","method":"prompts/list"}
```
The server's JSON-RPC response will appear on `stdout`. Server logs will appear on `stderr`.
*Example `add_prompt` tool call:*
```json
{"jsonrpc":"2.0","id":"add1","method":"tools/call","params":{"name":"add_prompt","arguments":{"id":"my-test-prompt","content":"Test content: {{var1}}","tags":["test"],"variables":{"var1":{"description":"A test variable"}}}}}
```
### 2. MCP Inspector
The [MCP Inspector](https://github.com/modelcontextprotocol/inspector) is a GUI tool that can connect to MCP servers.
* **To connect to a locally running server (compiled):**
```bash
mcp-inspector --stdio "node /path/to/your/mcp-promptregistry/dist/server.js"
```
* **To connect to the Docker container:**
```bash
mcp-inspector --stdio "docker run -i --rm mcp-promptregistry"
```
*(Replace `mcp-promptregistry` with your image name if different. Ensure `mcp-inspector` is installed and in your PATH.)*
The Inspector allows you to see available prompts and tools, make requests, and view responses interactively.
## 🧰 Using with Claude Desktop (Example Workflow)
Once MCP Prompt Registry is added as an MCP server in Claude Desktop (using one of the configurations above):
1. **Discover Prompts:** Your custom prompts should appear in Claude Desktop's prompt library or be accessible via its command interface (e.g., by typing `/` or similar, depending on Claude's UI). The `description` you set in your prompt's JSON file will be visible.
2. **Select a Prompt:** Choose one of your prompts.
3. **Fill Arguments:** If the prompt has variables (e.g., `{{concept}}`, `{{age}}`), Claude Desktop should provide UI fields for you to enter these values. The `description` for each variable (from your prompt's JSON) can guide the user.
4. **Execute:** Claude Desktop will send a `prompts/get` request to your server with the filled arguments. Your server will apply the template and return the final prompt content to Claude.
5. **Management Tools:** To use tools like `add_prompt` or `filter_prompts_by_tags` *from* Claude Desktop, Claude would need a way to send arbitrary `tools/call` requests to connected MCP servers. If this isn't directly supported, you'd typically use MCP Inspector or manual stdio alongside Claude for management tasks.
## 🛠️ Available Management Tools
Your MCP Prompt Registry exposes the following tools (callable via MCP `tools/call` requests):
* **`add_prompt`**: Adds a new prompt to the prompt directory.
* *Args:* `id`, `content`, `description` (optional), `tags` (optional), `variables` (optional), `metadata` (optional).
* **`get_prompt_file_content`**: Retrieves the raw JSON definition of the prompt.
* *Args:* `id`.
* **`update_prompt`**: Updates an existing prompt.
* *Args:* `id`, and any fields to update (`content`, `description`, etc.).
* **`delete_prompt`**: Deletes a prompt from the prompt directory.
* *Args:* `id`.
* **`filter_prompts_by_tags`**: Lists prompts that match *all* specified tags. Returns a summary (id, description, tags).
* *Args:* `tags` (array of strings).
* **`load_default_prompts`**: Copies all prompts from the `default_prompts_data/` directory (if present) into the active prompt directory, skipping any that already exist. Useful for populating or restoring default prompts.
* *Args:* None.
## example
## ⚠️ Troubleshooting & Gotchas
* **Stdio Server Logging:** Remember, `console.log()` in your `server.ts` will break MCP communication over stdio because it writes to `stdout`. All server-side diagnostic/status logs should use `console.error()`, which writes to `stderr`. For logs you want the client to potentially see, use MCP's logging capability via `context.sendNotification` in tool handlers (if the client supports it).
* **Server Startup Messages on Stderr:** Some initial server startup messages, such as directory creation or automatic default prompt loading, will appear on `stderr` (e.g., `Attempting to create prompt directory: /Users/stevengonsalvez/.promptregistry` or `Auto-loaded 2 default prompt(s) into ~/.promptregistry: code-review-assistant, prompt-writing-assistant`). This is because `stdout` is reserved for MCP JSON-RPC messages, and these startup actions occur before a client context is available for `sendNotification`.
* **Permissions:** Ensure the server process has write permissions for the prompt directory.
* **JSON Validity:** Ensure your prompt JSON files are valid.
* **Absolute Paths for Clients:** When configuring clients with local server paths, always use absolute paths.
## 🌱 Contributing & Future Ideas
This is a starting point! Future enhancements could include:
* More sophisticated templating.
* A watch mode to auto-reload prompts when files change.
* Support for other storage backends (e.g. postgres, github (or gists), sqllite).
Pull requests and ideas are welcome!
