Documentation: docs.toolfront.ai

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

Install toolfront with pip or your favorite PyPI package manager.

pip install toolfront

ToolFront helps you build and deploy environments for AI agents. Think of environments as interactive directories that agents can explore and take actions in.

environment
├── index.md
├── pages/
│   ├── database.md
│   ├── document.md
│   └── api.md
└── data/
    ├── receipt_20240115_001.txt
    └── receipt_20240118_002.txt

To add actions to an environment, simply define commands in any markdown header. As agents browse files, they will discover these tools and learn how to use them with the --help flag.

---
tools:
- [python3, cli.py]
- [curl, -X, GET, https://api.example.com/data]

---

# My environment page

Add [links](./page_1) to tell your agents what pages they should check out.

Agents can call any command defined in markdown headers.
- `python3 cli.py` executes a python script
- `curl -X GET https://api.example.com/data` calls an API

You can launch browsing sessions with ToolFront's Python SDK, or build your own browsing agent with the MCP. Browsing is always powered by your own models.

from toolfront import Browser

browser = Browser(model="openai:gpt-5")

url = "file:///path/to/environment"

answer = browser.ask("What's our average ticket price?", url=url)
print(answer)

{
  "mcpServers": {
    "toolfront": {
      "command": "uvx",
      "args": ["toolfront", "mcp", "file:///path/to/toolsite"]
    }
  }
}

ToolFront's comes with six core tools your agents can use to interact with environments:

• run_command - Execute commands defined in markdown headers
• read - Get the content of a specific page or file
• glob - List files matching a pattern
• tree - View directory structure
• grep - Search files using regex patterns
• search - Find relevant documents or lines*

*requires indexing environment files.

Instantly deploy your environments with ToolFront Cloud.

toolfront deploy ./path/to/environment --api-key "my-api-key"

Would give you a secure environment URL your agents can browse.

answer = browser.ask(..., url="https://cloud.toolfront.ai/user/environment")

Environments deployed with ToolFront Cloud are automatically indexed and get access to the powerful search tool.

Let me search the environment for documents relevant to "ticket pricing API"...

Found 3 relevant pages:
  - ./api/pricing.md (highly relevant)
  - ./guides/analytics.md (relevant)
  - ./examples/queries.md (somewhat relevant)

I'll start by reading ./api/pricing.md...

ToolFront Cloud is currently in open beta. To request access, join our Discord or email esteban[at]kruskal[dot]ai.

• Discord: Join our community server for real-time help and discussions
• X: Follow us @toolfront for updates and news
• Issues: Report bugs or request features on GitHub Issues

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