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ToolFront

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MCP server providing data environments for AI agents with organized workflows and tools

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ToolFront

Build AI Applications in Markdown

Test Suite PyPI package Discord X


Documentation: docs.toolfront.ai

Source code: https://github.com/statespace-tech/toolfront


Quickstart

ToolFront is a declarative framework for building AI agents in Markdown.

Write tools and instructions in .md files. Run the project and get a live AI application.

Create it

Start with one file: README.md

--- tools: - [curl, -X, GET, "https://httpbin.org/status/200"] --- # Status Checker - Use `curl` to check if the service is up

Run it

Run the application with:

toolfront run .

Ask it

Ask your agents about the application:

Python SDK
from toolfront import Application app = Application(url="http://127.0.0.1:8000") result = app.ask("Is the service up?", model="openai:gpt-5") print(result) # Answer: yes
MCP Server
{ "mcpServers": { "toolfront": { "command": "uvx", "args": ["toolfront", "mcp", "http://127.0.0.1:8000"] } } }

Upgraded Example

Your full project can grow like this:

project/ ├── README.md ├── src/ │ ├── api.md │ ├── rag.md │ ├── text2sql.md │ └── toolkit.md ├── data/ └── tools/

Add Navigation

Update README.md with tools to explore the project

--- tools: - [curl, -X, GET, "https://httpbin.org/status/200"] - [ls] - [cat] --- # Status Checker - Use `curl` to check if the service is up - Use `ls` and `cat` to browse other files

Add Document RAG

Give your agent tools to search documents

--- tools: - [grep] --- # Search Docs - Use `grep` to search files in `/data/`

Add Text-to-SQL

Connect your databases for SQL workflows

--- tools: - [psql, -U, $USER, -d, $DATABASE, -c, {query}] --- # Database Access - Call the `psql` tool to query the PostgreSQL database

Add Custom Tools

Build custom tools in any programming language

--- tools: - [python, tools/status.py, --delayed] --- # Custom Tools - Run `status.py` to check delayed orders

Installation

Install toolfront with your favorite PyPI package manager.

pip install toolfront

Deploy with ToolFront Cloud

Deploy your AI applications with ToolFront Cloud.

toolfront deploy ./path/to/project

This gives you a secure application URL you can access from anywhere.

app = Application(url="https://cloud.toolfront.ai/user/project", params={"API_KEY": ...})

ToolFront Cloud is in beta. To request access, join our Discord or email esteban[at]statespace[dot]com.

Community & Contributing

License

This project is licensed under the terms of the MIT license.

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