Datastore Server
БесплатноНе проверенEnables AI assistants to interact with Google Cloud Datastore, allowing them to create, read, update, delete entities, and perform queries with filtering and or
Описание
Enables AI assistants to interact with Google Cloud Datastore, allowing them to create, read, update, delete entities, and perform queries with filtering and ordering.
README
A Model Context Protocol (MCP) server that provides access to Google Cloud Datastore. This server enables AI assistants like Claude to interact with Datastore entities, perform queries, and manage data.
Features
- Entity Operations: Create, read, update, and delete Datastore entities
- Query Support: Execute queries with filters, ordering, and pagination
- Namespace Support: Work with different Datastore namespaces
- Emulator Support: Connect to local Datastore emulator by default for development
- Production Ready: Easy configuration for production Google Cloud Datastore
Installation
Prerequisites
Option 1: Docker (Recommended)
- Docker Engine 20.10+
- Docker Compose v2.0+
Option 2: Local Python
- Python 3.10 or higher
- Google Cloud Datastore emulator (for local development) or Google Cloud project (for production)
Install from source
# Clone the repository
git clone <repository-url>
cd datastore-mcp
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -e .
Using uv (recommended)
# Create virtual environment and install dependencies
uv venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
uv pip install -e .
Using Docker (recommended for testing)
Docker provides an isolated environment with both the Datastore emulator and MCP server pre-configured.
# Run tests
make test
# Start all services (emulator + server)
make up
# View logs
make logs
# Stop services
make down
For detailed Docker documentation, see DOCKER.md.
Configuration
The server can be configured using environment variables or command-line arguments.
Environment Variables
For Emulator:
DATASTORE_DATASET- Dataset name (default:test)DATASTORE_EMULATOR_HOST- Datastore emulator host (default:localhost:8081)DATASTORE_EMULATOR_HOST_PATH- Emulator host path (default:localhost:8081/datastore)DATASTORE_HOST- Datastore HTTP host (default:http://localhost:8081)DATASTORE_PROJECT_ID- Google Cloud project ID (default:test)DATASTORE_NAMESPACE- Default namespace (optional)
For Production:
DATASTORE_PROJECT_ID- Google Cloud project ID (required)GOOGLE_APPLICATION_CREDENTIALS- Path to service account key file (required)DATASTORE_NAMESPACE- Default namespace (optional)
Running with Datastore Emulator (Default)
# Start the Datastore emulator (in a separate terminal)
gcloud beta emulators datastore start --host-port=localhost:8081
# Run the MCP server (uses emulator by default)
python src/datastore_mcp/server.py
# Or with custom emulator host
DATASTORE_EMULATOR_HOST=localhost:9090 python src/datastore_mcp/server.py
Running with Production Datastore
# Set credentials and project
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account-key.json
export DATASTORE_PROJECT_ID=your-gcp-project-id
# Unset emulator host to use production
unset DATASTORE_EMULATOR_HOST
# Run the server
python src/datastore_mcp/server.py
Usage with Claude Desktop
Add this configuration to your Claude Desktop config file:
MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
For Emulator (Development)
{
"mcpServers": {
"datastore": {
"command": "python",
"args": ["/path/to/datastore-mcp/src/datastore_mcp/server.py"],
"env": {
"DATASTORE_DATASET": "test",
"DATASTORE_EMULATOR_HOST": "localhost:8081",
"DATASTORE_EMULATOR_HOST_PATH": "localhost:8081/datastore",
"DATASTORE_HOST": "http://localhost:8081",
"DATASTORE_PROJECT_ID": "test"
}
}
}
}
For Production
{
"mcpServers": {
"datastore": {
"command": "python",
"args": ["/path/to/datastore-mcp/src/datastore_mcp/server.py"],
"env": {
"DATASTORE_PROJECT_ID": "your-gcp-project-id",
"GOOGLE_APPLICATION_CREDENTIALS": "/path/to/service-account-key.json"
}
}
}
}
Using Docker with Claude Desktop (Recommended)
Option 1: Fully Automated (Emulator + Server)
Use the provided wrapper script (included in the repository):
MacOS/Linux: start-datastore-mcp.sh
Windows: start-datastore-mcp.bat
Then configure Claude Desktop:
MacOS/Linux:
{
"mcpServers": {
"datastore": {
"command": "/path/to/datastore-mcp/start-datastore-mcp.sh"
}
}
}
Windows:
{
"mcpServers": {
"datastore": {
"command": "C:\\path\\to\\datastore-mcp\\start-datastore-mcp.bat"
}
}
}
This option automatically starts the emulator if it's not running and waits for it to be healthy before starting the MCP server.
Option 2: Manual Emulator Start
First, start the Datastore emulator once:
cd /path/to/datastore-mcp
make emulator-only # Keeps running in background
Then configure Claude Desktop:
{
"mcpServers": {
"datastore": {
"command": "docker",
"args": [
"compose",
"-f",
"/path/to/datastore-mcp/docker-compose.yml",
"run",
"--rm",
"mcp-server"
]
}
}
}
Option 3: External Emulator (Custom IP)
If your emulator runs on a different machine or custom IP:
{
"mcpServers": {
"datastore": {
"command": "docker",
"args": [
"compose",
"-f",
"/path/to/datastore-mcp/docker-compose.yml",
"run",
"--rm",
"-e", "DATASTORE_EMULATOR_HOST=localhost:8081",
"-e", "DATASTORE_EMULATOR_HOST_PATH=localhost:8081/datastore",
"-e", "DATASTORE_HOST=http://localhost:8081",
"mcp-server"
]
}
}
}
Using uv with Claude Desktop
{
"mcpServers": {
"datastore": {
"command": "uv",
"args": [
"--directory",
"/path/to/datastore-mcp",
"run",
"datastore-mcp"
],
"env": {
"DATASTORE_DATASET": "test",
"DATASTORE_EMULATOR_HOST": "localhost:8081",
"DATASTORE_EMULATOR_HOST_PATH": "localhost:8081/datastore",
"DATASTORE_HOST": "http://localhost:8081",
"DATASTORE_PROJECT_ID": "test"
}
}
}
}
Available Tools
Once connected, the following tools are available to Claude:
datastore_get- Retrieve an entity by keydatastore_put- Create or update an entitydatastore_delete- Delete an entitydatastore_query- Query entities with filters and orderingdatastore_batch_get- Retrieve multiple entities by keysdatastore_list_kinds- List all entity kinds in the namespace
Example Queries
Ask Claude to:
- "Get the User entity with ID 12345"
- "Query all Products where price > 100, ordered by name"
- "Create a new BlogPost entity with title and content"
- "Delete the Comment entity with ID abc123"
- "List all entity kinds in my datastore"
Development
Using Docker (Recommended)
# Run tests
make test
# Run tests with coverage
docker-compose run --rm test
# Start emulator only for local development
make emulator-only
# Interactive shell in container
make shell
Using Local Python
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
# Run tests with coverage
pytest --cov=src/datastore_mcp --cov-report=term-missing
# Run the server
python src/datastore_mcp/server.py
Project Structure
datastore-mcp/
├── src/
│ └── datastore_mcp/
│ ├── server.py # Main MCP server
│ ├── datastore.py # Datastore client wrapper
│ └── tools.py # Tool implementations
├── tests/
│ └── test_tools.py
├── pyproject.toml
└── README.md
License
MIT License
Contributing
Contributions are welcome! Please open an issue or submit a pull request.
Установка Datastore Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/hashkrish/datastore-mcpFAQ
Datastore Server MCP бесплатный?
Да, Datastore Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Datastore Server?
Нет, Datastore Server работает без API-ключей и переменных окружения.
Datastore Server — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Datastore Server в Claude Desktop, Claude Code или Cursor?
Открой Datastore Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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