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.
• 🔒 Privacy-first: Your data never leaves your machine, 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.

Quickstart

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

Prerequisites

You'll need uv or Docker to run the MCP server, and optionally an API key to activate collaborative learning.

Running with UV:

Add this to your MCP config file to connect coding agents to ToolFront with UV:

{
  # Rest of config file
  "toolfront": {
    "command": "uvx",
    "args": [
      "toolfront",
      "DATABASE-URL-1",
      "DATABASE-URL-2",
      # Add other database URLs here
      "--api-key", "YOUR-API-KEY"  // Optional
    ]
  }
}

Alternatively, run uvx toolfront to download and start the ToolFront MCP server:

uvx toolfront "DATABASE-URL-1" "DATABASE-URL-2" [...] --api-key "YOUR-API-KEY"

[!TIP]Version control: Use toolfront to get the latest version automatically, or pin to a specific version e.g. toolfront==0.1.0. This applies to both direct commands and MCP configuration.

Running with Docker

Add this to your MCP config file to connect coding agents to ToolFront with Docker:

{
  # Rest of config file
  "toolfront": {
    "command": "docker",
    "args": [
      "run",
      "-i",
      "antidmg/toolfront",
      "DATABASE-URL-1",
      "DATABASE-URL-2",
      # Add other database URLs here
      "--api-key", "YOUR-API-KEY"  // Optional
    ]
  }
}

[!TIP]Localhost databases: When connecting to databases on localhost (like postgresql://user:pass@localhost:5432/db), add --network host before the image name. Remote databases (cloud, external servers) work without this flag.

Alternatively, run the following command to download, pull, and run the ToolFront MCP container:

docker run -i antidmg/toolfront "DATABASE-URL-1" "DATABASE-URL-2" [...] --api-key "YOUR-API-KEY"

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].

Model Context Protocol (MCP)

ToolFront's MCP server comes with seven database tools for AI agents.

Databases

When configuring ToolFront, use the fully-specified connection URL for your databases:

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

Tools

ToolFront provides AI agents with the following database tools:

FAQ

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.

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.

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.

• 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

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:

• Discord: Join our community server for real-time help and discussions
• Issues: Report bugs or request features on GitHub Issues

Contributing

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

License

ToolFront is released under the GPL License v3. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the GPL v3 License. For the full license text, see the LICENSE file in the repository.