MCP Server for SurrealDB - Bridge AI assistants with SurrealDB databases
Project description
SurrealDB MCP Server
A Model Context Protocol (MCP) server that enables AI assistants to interact with SurrealDB databases
=� Overview
The SurrealDB MCP Server bridges the gap between AI assistants and SurrealDB, providing a standardized interface for database operations through the Model Context Protocol. This enables LLMs to:
- Execute complex SurrealQL queries
- Perform CRUD operations on records
- Manage graph relationships
- Handle bulk operations efficiently
- Work with SurrealDB's unique features like record IDs and graph edges
Features
- Full SurrealQL Support: Execute any SurrealQL query directly
- Comprehensive CRUD Operations: Create, read, update, delete with ease
- Graph Database Operations: Create and traverse relationships between records
- Bulk Operations: Efficient multi-record inserts
- Smart Updates: Full updates, merges, and patches
- Type-Safe: Proper handling of SurrealDB's RecordIDs
- Connection Pooling: Efficient database connection management
- Multi-Database Support: Override namespace/database per tool call
- Detailed Documentation: Extensive docstrings for AI comprehension
=� Prerequisites
- Python 3.10 or higher
- SurrealDB instance (local or remote)
- MCP-compatible client (Claude Desktop, MCP CLI, etc.)
=� Installation
Using uvx (Simplest - No Installation Required)
# Run directly from PyPI (once published)
uvx surreal-mcp
# Or run from GitHub
uvx --from git+https://github.com/yourusername/surreal-mcp.git surreal-mcp
Using uv (Recommended for Development)
# Clone the repository
git clone https://github.com/yourusername/surreal-mcp.git
cd surreal-mcp
# Install dependencies
uv sync
# Run the server (multiple ways)
uv run surreal-mcp
# or
uv run python -m surreal_mcp
# or
uv run python main.py
Using pip
# Clone the repository
git clone https://github.com/yourusername/surreal-mcp.git
cd surreal-mcp
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install package
pip install -e .
# Run the server
surreal-mcp
# or
python -m surreal_mcp
� Configuration
The server uses environment variables for configuration.
Required Variables (at startup)
| Variable | Description | Example |
|---|---|---|
SURREAL_URL |
SurrealDB connection URL | ws://localhost:8000/rpc |
SURREAL_USER |
Database username | root |
SURREAL_PASSWORD |
Database password | root |
Optional Variables (can be overridden per tool call)
| Variable | Description | Example |
|---|---|---|
SURREAL_NAMESPACE |
Default SurrealDB namespace | test |
SURREAL_DATABASE |
Default SurrealDB database | test |
Note: If
SURREAL_NAMESPACEandSURREAL_DATABASEare not set as environment variables, you must providenamespaceanddatabaseparameters in each tool call.
Setting Environment Variables
You can copy .env.example to .env and update with your values:
cp .env.example .env
# Edit .env with your database credentials
Or set them manually:
export SURREAL_URL="ws://localhost:8000/rpc"
export SURREAL_USER="root"
export SURREAL_PASSWORD="root"
export SURREAL_NAMESPACE="test"
export SURREAL_DATABASE="test"
MCP Client Configuration
Add to your MCP client settings (e.g., Claude Desktop):
Using uvx (recommended):
{
"mcpServers": {
"surrealdb": {
"command": "uvx",
"args": ["surreal-mcp"],
"env": {
"SURREAL_URL": "ws://localhost:8000/rpc",
"SURREAL_USER": "root",
"SURREAL_PASSWORD": "root",
"SURREAL_NAMESPACE": "test",
"SURREAL_DATABASE": "test"
}
}
}
}
Using local installation:
{
"mcpServers": {
"surrealdb": {
"command": "uv",
"args": ["run", "surreal-mcp"],
"env": {
"SURREAL_URL": "ws://localhost:8000/rpc",
"SURREAL_USER": "root",
"SURREAL_PASSWORD": "root",
"SURREAL_NAMESPACE": "test",
"SURREAL_DATABASE": "test"
}
}
}
}
=' Available Tools
All tools support optional namespace and database parameters to override the default values from environment variables.
1. query
Execute raw SurrealQL queries for complex operations.
-- Example: Complex query with graph traversal
SELECT *, ->purchased->product FROM user WHERE age > 25
# Query with namespace/database override
query("SELECT * FROM user", namespace="production", database="main")
2. select
Retrieve all records from a table or a specific record by ID.
# Get all users
select("user")
# Get specific user
select("user", "john")
# Select from a different database
select("user", namespace="other_ns", database="other_db")
3. create
Create a new record with auto-generated ID.
create("user", {
"name": "Alice",
"email": "alice@example.com",
"age": 30
})
4. update
Replace entire record content (preserves ID and timestamps).
update("user:john", {
"name": "John Smith",
"email": "john.smith@example.com",
"age": 31
})
5. delete
Permanently remove a record from the database.
delete("user:john")
6. merge
Partially update specific fields without affecting others.
merge("user:john", {
"email": "newemail@example.com",
"verified": True
})
7. patch
Apply JSON Patch operations (RFC 6902) to records.
patch("user:john", [
{"op": "replace", "path": "/email", "value": "new@example.com"},
{"op": "add", "path": "/verified", "value": True}
])
8. upsert
Create or update a record with specific ID.
upsert("settings:global", {
"theme": "dark",
"language": "en"
})
9. insert
Bulk insert multiple records efficiently.
insert("product", [
{"name": "Laptop", "price": 999.99},
{"name": "Mouse", "price": 29.99},
{"name": "Keyboard", "price": 79.99}
])
10. relate
Create graph relationships between records.
relate(
"user:john", # from
"purchased", # relation name
"product:laptop-123", # to
{"quantity": 1, "date": "2024-01-15"} # relation data
)
=� Examples
Basic CRUD Operations
# Create a user
user = create("user", {"name": "Alice", "email": "alice@example.com"})
# Update specific fields
merge(user["id"], {"verified": True, "last_login": "2024-01-01"})
# Query with conditions
results = query("SELECT * FROM user WHERE verified = true ORDER BY created DESC")
# Delete when done
delete(user["id"])
Working with Relationships
# Create entities
user = create("user", {"name": "John"})
product = create("product", {"name": "Laptop", "price": 999})
# Create relationship
relate(user["id"], "purchased", product["id"], {
"quantity": 1,
"total": 999,
"date": "2024-01-15"
})
# Query relationships
purchases = query(f"SELECT * FROM {user['id']}->purchased->product")
Bulk Operations
# Insert multiple records
products = insert("product", [
{"name": "Laptop", "category": "Electronics", "price": 999},
{"name": "Mouse", "category": "Electronics", "price": 29},
{"name": "Desk", "category": "Furniture", "price": 299}
])
# Bulk update with query
query("UPDATE product SET on_sale = true WHERE category = 'Electronics'")
<<<<<<< HEAD
<� Architecture
=======
Multi-Database Operations
You can work with multiple databases in a single session by using the namespace and database parameters:
# Create a record in the production database
create("user", {"name": "Alice"}, namespace="prod", database="main")
# Query from staging database
select("user", namespace="staging", database="main")
# Copy data between databases
users = select("user", namespace="staging", database="main")
for user in users["data"]:
create("user", user, namespace="prod", database="main")
Behavior Summary:
| Scenario | Result |
|---|---|
| Env vars set, no params | Uses pooled connection (best performance) |
| Env vars set, params provided | Uses override connection with specified namespace/database |
| No env vars, params provided | Uses override connection with specified namespace/database |
| No env vars, no params | Fails with clear error message |
<� Architecture
main
The server is built with:
- FastMCP: Simplified MCP server implementation
- SurrealDB Python SDK: Official database client
- Connection Pooling: Efficient connection management
- Async/Await: Non-blocking database operations
>� Testing
The project includes a comprehensive test suite using pytest.
Prerequisites
- SurrealDB instance running locally
- Test database access (uses temporary test databases)
Running Tests
# Make sure SurrealDB is running
surreal start --user root --pass root
# Run all tests
uv run pytest
# Run with coverage
uv run pytest --cov=surreal_mcp
# Run specific test file
uv run pytest tests/test_tools.py
# Run specific test class or method
uv run pytest tests/test_tools.py::TestQueryTool
uv run pytest tests/test_tools.py::TestQueryTool::test_query_simple
# Run with verbose output
uv run pytest -v
# Run only tests matching a pattern
uv run pytest -k "test_create"
Test Structure
tests/
├── __init__.py
├── conftest.py # Fixtures and test configuration
├── test_tools.py # Tests for all MCP tools
├── test_server.py # Tests for server configuration
└── test_namespace_override.py # Tests for namespace/database override
Writing Tests
The test suite includes fixtures for common test data:
clean_db- Ensures clean database statesample_user_data- Sample user datacreated_user- Pre-created user recordcreated_product- Pre-created product record
Example test:
@pytest.mark.asyncio
async def test_create_user(clean_db, sample_user_data):
result = await mcp._tools["create"].func(
table="user",
data=sample_user_data
)
assert result["success"] is True
assert result["data"]["email"] == sample_user_data["email"]
> Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
=� License
This project is licensed under the MIT License - see the LICENSE file for details.
=O Acknowledgments
- SurrealDB for the amazing graph database
- FastMCP for simplifying MCP server development
- Model Context Protocol for the standardized AI-tool interface
=� Support
- =� Email: your.email@example.com
- =� Discord: Join our server
- = Issues: GitHub Issues
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