Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@PromptVault MCP Server Create a new prompt called 'summarize' with the content 'Summarize this: {input}'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Open-source prompt versioning, evaluation, and management as an MCP server.
PromptVault is a self-hosted tool for AI engineers and prompt engineers to:
Version prompts like code with immutable versions and rollback support
Evaluate prompts against datasets using LLM providers (OpenAI, Anthropic, Ollama)
Access everything through an MCP server, CLI, or REST API
Related MCP server: PromptingBox MCP Server
pip install pvltOr with uv/pipx:
uvx --from git+https://github.com/KrishBnsl/promptVault.git promptctl --helpOr with Docker:
docker run -p 8000:8000 -e GEMINI_API_KEY=your-key ghcr.io/krishbnsl/pvltgit clone https://github.com/KrishBnsl/promptVault.git
cd promptVault
uv sync
cp .env.example .env
# Edit .env with your API keyspromptctl prompt create summarize \
--content "Summarize the following article in {tone} style:\n\n{article}" \
--description "Summarizes an article" \
--variables '{"tone": "concise", "article": "string"}' \
--model-config '{"provider": "openai", "model": "gpt-4o-mini", "temperature": 0.2}' \
--tags "summarization,content"echo '{"input": {"article": "AI is transforming..."}, "expected_output": "AI transforms..."}' > dataset.jsonl
promptctl dataset create article-summaries --file dataset.jsonlpromptctl eval run summarize --dataset article-summariesAdd to your Claude Desktop config:
{
"mcpServers": {
"pvlt": {
"command": "promptctl",
"args": ["serve"]
}
}
}promptctl prompt create <name> --content <text> [options]
promptctl prompt update <name> --content <text> [options]
promptctl prompt list [--tags TAGS] [--limit N]
promptctl prompt show <name> [--version N]
promptctl prompt versions <name>
promptctl prompt diff <name> <version-a> <version-b>
promptctl prompt rollback <name> --version N
promptctl dataset create <name> --file <jsonl-or-json>
promptctl dataset list
promptctl eval run <prompt-name> --dataset <dataset-name>
promptctl eval report <evaluation-id>
promptctl serve [--stdio|--http] [--port 8000]
promptctl web [--port 8080]Tool | Description |
| Create a new prompt with initial version |
| Create the next immutable prompt version |
| Retrieve a prompt version |
| List all prompts |
| List all versions of a prompt |
| Diff two prompt versions |
| Rollback to a previous version |
| Create a dataset |
| List datasets |
| Get dataset with items |
| Run evaluation |
| Check evaluation status |
| Get evaluation report |
| Compare two evaluations |
Base URL: http://localhost:8000/api
# Create a prompt
curl -X POST http://localhost:8000/api/prompts \
-H "Content-Type: application/json" \
-d '{"name": "test", "content": "Hello {name}"}'
# List prompts
curl http://localhost:8000/api/prompts
# Get a prompt
curl http://localhost:8000/api/prompts/testCopy .env.example to .env and configure:
PROMPTVAULT_DB_PATH=./promptvault.db
PROMPTVAULT_DEFAULT_PROVIDER=openai
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GEMINI_API_KEY=...
OLLAMA_BASE_URL=http://localhost:11434┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ MCP Client │ │ CLI │ │ REST Client │
│ (Claude etc) │ │ (promptctl) │ │ (curl, apps) │
└──────┬──────┘ └──────┬──────┘ └──────┬──────┘
│ │ │
▼ ▼ ▼
┌─────────────────────────────────────────────────┐
│ PromptVault Core │
│ ┌─────────────┐ ┌──────────────┐ ┌──────────┐ │
│ │ Versioning │ │ Evaluation │ │ Storage │ │
│ │ Engine │ │ Engine │ │ Layer │ │
│ └─────────────┘ └──────────────┘ └──────────┘ │
│ ┌──────────────────────────────────────────┐ │
│ │ SQLite Database (local) │ │
│ └──────────────────────────────────────────┘ │
└─────────────────────────────────────────────────┘📖 Full docs: https://krishbnsl.github.io/promptVault/
MIT License - see LICENSE for details.
This server cannot be deployed
Manage, version, and publish LLM prompts with blocks, variables, and evaluations.
Generate contextual prompts and reusable agent skills, evaluate prompts with the 16-dimension Prompt Score, and manage saved work in PromptDrive. Twelve MCP tools also provide authorized access to private Memory for source-grounded answers. Connect over Streamable HTTP using OAuth 2.1 and PKCE. Generation consumes account quota and automatically saves successful results; Memory access follows account permissions and plan limits.
Self-hosted AI prompt library: prompts, collections, tags, teams, chains. 29 MCP tools for agents.
Professional prompt library over remote MCP: 13 verticals, free discovery scope.
