
Spotdb
ai.aliengiraffePublished by aliengiraffe.aiv0.1.0Updated Oct 24, 2026
Ephemeral data sandbox for AI workflows with guardrails and security
Overview
SpotDB is a local ephemeral data sandbox that lets an AI assistant load CSV data and run SQL queries in an isolated environment instead of production databases.
- What you can do
- Load CSV files into temporary tables in a local sandbox database and query them with SQL through the MCP endpoint, with a REST API and browser Explorer UI for the same upload and query workflow. Capture snapshots to recover point-in-time data states or continue from a previous state. Apply guardrails and access controls intended to prevent accidental data modification and keep exploration isolated from production systems.
- When to use it
- Useful when an assistant needs to explore or analyze tabular data, such as uploaded CSV files, without touching production databases, and when you want a disposable sandbox with snapshot and rollback for agentic data workflows.
- Requirements
- Runs as a local process on the user's machine, installed via Homebrew and started with the spotdb command; the MCP connection is added through npx mcp-remote against a local stream endpoint. An optional X-API-Key environment variable can be set for request authentication. Desktop only.
Installation
In SourceWeft
- Open Spotdb in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
SpotDB
Lightweight data sandbox for AI workflows and data exploration, enabled with guardrails and security to keep your data safe.
This project provides a lightweight, ephemeral data sandbox designed for large language models (LLMs) and agentic workflows. By providing a secure, isolated environment, it allows AI agents and scripts to analyze data without direct access to production databases. This setup prevents accidental data modification, ensures data privacy, and enforces guardrails for safe data exploration.
Features
- 🏖️ Ephemeral Data Sandbox: Create temporary databases for AI workflows and data exploration.
- 📸 Snapshot: Capture and store data snapshots, recover point-in-time data states or continue from a previous state.
- 🧠 MCP API: Access data through a Model Context Protocol for seamless integration with AI models and agentic workflows.
- ⚙️ REST API: Access data through a RESTful API for integration with traditional systems and workflows.
- 🚂 Guardrails: Enforce rules and constraints to ensure data safety and privacy.
- 🛡️ Security: Protect data from unauthorized access and modification.
Quick Start
- Tap the repository and install the package:
- Start the server:
- Upload a CSV file:
- Query the data:
- Setup Claude Code
You must have the
claudecommand installed.
Then, you can add the spotdb mcp:
Use Explorer UI
Open the Explorer UI in your browser and upload files and query the data:
Full Documentation
Source: README.md at commit cfbbef2
Tools
0Version history
1- v0.1.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts