MCP ExplorerExplorer

Toolfront

@kruskal-labson 10 days ago
14 GPL-3.0
FreeCommunity
AI Systems
#ai-agents#data-analysis#data-engineering#data-science#databases#mcp#database-management#in-context-learning
A lightweight MCP server for databases.

Overview

What is Toolfront

ToolFront is a lightweight MCP server designed to connect AI agents with databases, enabling collaborative learning and efficient query management.

Use cases

Use cases include streamlining database query processes, improving team collaboration on data-related tasks, and enhancing AI agents’ contextual understanding of database interactions.

How to use

To use ToolFront, install it on your computer using either UV or Docker. Connect your coding agents like Cursor or GitHub Copilot to your databases with a single command.

Key features

Key features include one-step setup for connecting coding agents, a privacy-first approach ensuring data remains on your machine, and collaborative learning that enhances AI agents’ understanding of your databases over time.

Where to use

ToolFront is suitable for software development, data analysis, and any field where teams need to manage database queries efficiently and collaboratively.

Content

Test Suite
Discord


toolfront

AI agents lack context about your databases, while teams keep rewriting the same queries because past work often gets lost.
ToolFront connects agents to your databases and feeds them your team’s proven query patterns, so both agents and teammates can learn from each other and ship faster.

Features

  • ⚡ One-step setup: Connect coding agents like Cursor, GitHub Copilot, and Claude to all your databases with a single command or config.
  • 🔒 Privacy-first: Your data never leaves your premises, and is only shared between agents and databases through a secure MCP server.
  • 🧠 Collaborative learning: The more your team uses ToolFront, the better your AI agents understand your databases and query patterns. Requires API key.

databases

Quickstart

ToolFront runs on your computer through an MCP server, a secure protocol that lets apps provide context to LLM models.

Prerequisites

  • uv or Docker to run the MCP server (we recommend uv)
  • Database connection URLs of your databases - see below
  • API key (optional) to activate collaborative learning - see below

Run ToolFront in your IDE

Add to Cursor with UV Add to GitHub Copilot with UV Add to Cursor with Docker Add to GitHub Copilot with Docker

First, create an MCP config by clicking a setup button above or navigating to the MCP settings for your IDE:

IDE Setup Instructions Documentation
Cursor Settings → Cursor Settings → MCP Tools (or create .cursor/mcp.json file) Cursor Documentation
GitHub Copilot (VSCode) Copilot icon → Edit preferences → Copilot Chat → MCP GitHub Copilot Documentation
Windsurf Plugins icon → Plugin Store → Add manually (or edit ~/.codeium/windsurf/mcp_config.json) Windsurf Documentation
Claude Code Run claude mcp add toolfront uvx toolfront [database-urls] --api-key YOUR-API-KEY Claude Code Documentation

Then, edit the MCP configuration with your database connection URLs and optional API key:

Edit UV Config
Edit Docker Config

You’re all set! You can now ask your coding assistant about your databases.

[!TIP]
Version control: You can pin to specific versions for consistency. Use toolfront==0.1.x for UV or antidmg/toolfront:0.1.x for Docker.

Run ToolFront from your Terminal

To use ToolFront outside your IDE, run it directly from your terminal with your database URLs and optional API key:

# Using UV
uvx toolfront "snowflake://user:pass@org" "postgresql://user:pass@host:port/db" --api-key "YOUR-API-KEY"

# Using Docker  
docker run -i antidmg/toolfront "snowflake://user:pass@org" "postgresql://user:pass@host:port/db" --api-key "YOUR-API-KEY"

[!TIP]
Localhost databases: Add --network host before the image name when connecting to databases running on localhost.

Collaborative In-context Learning

Data teams keep rewriting the same queries because past work often gets siloed, scattered, or lost. ToolFront teaches AI agents how your team works with your databases through in-context learning. With ToolFront, your agents can:

  • Reason about historical query patterns
  • Remember relevant tables and schemas
  • Reference your and your teammates’ work

[!NOTE]
In-context learning is currently in open beta. To request an API key, please email Esteban at [email protected] or hop into our Discord server.

Databases

ToolFront supports the following databases:

Database URL Format Documentation
BigQuery bigquery://{project-id}?credentials_path={path-to-service-account.json} Google Cloud Docs
Databricks databricks://token:{token}@{workspace}.cloud.databricks.com/{catalog}?http_path={warehouse-path} Databricks Docs
DuckDB duckdb://{path-to-database.duckdb} DuckDB Docs
MySQL mysql://{user}:{password}@{host}:{port}/{database} MySQL Docs
PostgreSQL postgres://{user}:{password}@{hostname}:{port}/{database-name} PostgreSQL Docs
Snowflake snowflake://{user}:{password}@{account}/{database} Snowflake Docs
SQL Server mssql://{user}:{password}@{server}:{port}/{database} or sqlserver://{user}:{password}@{server}:{port}/{database} SQL Server Docs
SQLite sqlite://{path-to-database.sqlite} SQLite Docs

Don’t see your database? Submit an issue or pull request, or let us know in our Discord!

[!TIP]
SSH tunneling: For databases behind SSH bastions, add SSH parameters to your URL: postgresql://user:pass@db:5432/database?ssh_host=bastion&ssh_user=ubuntu&ssh_password=pass or use ssh_key_path=/path/to/key.pem for key authentication.

Working with local data files? Add duckdb://:memory: to your config to analyze local Parquet, CSV, Excel, or JSON files.

Tools

MCP tools are functions that AI agents can call to interact with external systems. ToolFront comes with seven database tools:

Tool Description Requires API Key
test Tests whether a data source connection is working ✗
discover Discovers and lists all configured databases and file sources ✗
scan Searches for tables using regex, fuzzy matching, or TF-IDF similarity ✗
inspect Inspects table schemas, showing column names, data types, and constraints ✗
sample Retrieves sample rows from tables to understand data content and format ✗
query Executes read-only SQL queries against databases with error handling ✗
learn Retrieves relevant queries or tables for in-context learning ✓

FAQ

How is ToolFront different from other database MCPs?

ToolFront has three key advantages: multi-database support, privacy-first architecture, and collaborative learning.

Multi-database support: While some general-purpose MCP servers happen to support multiple databases, most database MCPs only work with one database at a time, forcing you to manage separate MCP servers for each connection. ToolFront connects to all your databases in one place.

Privacy-first architecture: Other multi-database solutions route your data through the cloud, which racks up egress fees and creates serious privacy, security, and access control issues. ToolFront keeps everything local.

Collaborative learning: Database MCPs just expose raw database operations. ToolFront goes further by teaching your AI agents successful query patterns from your team’s work, helping them learn your specific schemas and data relationships to improve over time.

How is collaborative learning different from agent memory?

Agent memory stores conversation histories for individuals, whereas ToolFront’s collaborative learning remembers relational query patterns across your team and databases.

When one teammate queries a database, that knowledge becomes available to other team members using ToolFront. The system gets smarter over time by learning from your team’s collective database interactions.

What data is collected during collaborative learning?

With an API key, ToolFront only logs the query syntax and their descriptions generated by your AI agents. It never collects your actual database content or personal information. For details, see the query and learn functions in tools.py.

How does ToolFront keep my data safe?
  • Local execution: All database connections and queries run on your machine
  • No secrets exposure: Database credentials are never shared with AI agents
  • Read-only operations: Only safe, read-only database queries are allowed
  • No data transmission: Your database content never leaves your environment
  • Secure MCP protocol: Direct communication between agents and databases with no third-party storage
How do I troubleshoot connection issues?

Run the uvx toolfront or docker run commands with your database URLs directly from the command line. ToolFront automatically tests all connections before starting and shows detailed error messages if any connection fails.

If you’re still having trouble, double-check your database URLs using the examples in the Databases section above.

Support & Community

Need help with ToolFront? We’re here to assist:

Contributing

See CONTRIBUTING.md for guidelines on how to contribute to ToolFront.

License

ToolFront is released under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For the full license text, see the LICENSE file in the repository.

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