Offers community support through a Discord server for real-time help and discussions
Offers containerized deployment of the ToolFront MCP server through Docker images
Provides connection to DuckDB databases, allowing AI agents to execute queries and explore DuckDB data
Provides issue tracking and repository hosting for the ToolFront project
Enables GitHub Copilot to connect to your databases, providing context about tables, schemas, and query patterns
Enables connections to MySQL databases, allowing AI agents to query and analyze MySQL data
Provides connection to PostgreSQL databases, allowing AI agents to query and work with PostgreSQL data
Enables connections to Snowflake data warehouses, allowing AI agents to query and analyze Snowflake data
Provides connection to SQLite databases, allowing AI agents to query and analyze SQLite data
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.
Step 1: Choose Your Method
You'll need uv or Docker to run the MCP server, and optionally an API key to activate collaborative learning. UV is recommended for most user as it automatically handles dependencies, while Docker is ideal for containerized environments.
Step 2: Setup ToolFront
Option A: One-Click Setup
Click one of these buttons to automatically configure ToolFront in your IDE:
Using UV:
Using Docker:
Option B: Manual Configuration
Add this configuration to your AI assistant's MCP settings:
Using UV:
Using Docker:
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.
Where to add the configuration:
- Cursor:
- Settings → Cursor Settings → MCP Tools
- Create
.cursor/mcp.json
file (project-specific) or~/.cursor/mcp.json
(global) - See Cursor's MCP documentation
- GitHub Copilot:
- Copilot icon → Edit preferences → Copilot Chat → MCP
- See GitHub Copilot's MCP documentation
- Windsurf:
- Plugins icon (top right) → Plugin Store → Add manually
- Edit
~/.codeium/windsurf/mcp_config.json
file - See Windsurf's MCP documentation
- Claude Code:
- Use CLI command
claude mcp add toolfront uvx toolfront [database-urls] --api-key YOUR-API-KEY
- See Claude Code's MCP documentation
- Use CLI command
Option C: Command Usage
Run ToolFront directly in your terminal:
Tip
Localhost databases: When using Docker with localhost databases, add --network host
before the image name.
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 esteban@kruskal.ai.
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:
Database | URL Example |
---|---|
BigQuery | bigquery://project/dataset |
DuckDB | duckdb:///path/to/db.duckdb |
MySQL | mysql://user:pass@host:port/db |
PostgreSQL | postgresql://user:pass@host:port/db |
Snowflake | snowflake://user:pass@account/db |
SQLite | sqlite:///path/to/db.sqlite |
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:
Tool | Description |
---|---|
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
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.
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
Securely connects AI agents to multiple databases simultaneously while enabling collaborative learning from team query patterns, all while keeping data private by running locally.
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