ToolFlow

中文 | English

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Stop building workflows. Write a function, ship a tool.

ToolFlow is a runtime-first MCP tool system for LLM applications. You write plain Python functions — ToolFlow handles versioning, dispatch, isolation, and dynamic composition at runtime.

No DAGs. No pipelines. No restarts. Tools are loaded, executed, and destroyed on demand in isolated sandboxes. Compose them dynamically when called, not when deployed.

Built on Django (control plane) + FastMCP (stateless execution layer).

Key Features

• 🐍 Python-native tools — write a function, register a tool. No boilerplate.
• ⚡ Dynamic composition — tools combine at runtime, not at design time.
• 🔒 Ephemeral sandboxes — every call runs in a fresh in-process sandbox with restricted imports; tool state is not reused across calls, though external side effects (for example, network calls) are still possible.
• 🧱 Control plane / execution plane separation — Django manages assets; FastMCP executes statelessly.
• 🔄 Built-in lifecycle management — version, release, and monitor tools independently.

Architecture & Invocation Flow

1. Architecture Flowchart

graph TD
  A[LLM / Client] -->|Tool Call| B[Django Gateway + Control Plane]
  B -->|Fetch Tool Code/Version| C["DB / Storage"]
  B -->|Dispatch Tasks| D{Queue/Dispatcher}
  D --> E[FastMCP Executor 1]
  D --> F[FastMCP Executor N]
  E -->|Ephemeral Load + Execute| G[Ephemeral Tool Runtime Sandbox]
  F -->|Ephemeral Load + Execute| H[Ephemeral Tool Runtime Sandbox]
  E -->|Report Status/Result| B
  F -->|Report Status/Result| B

Project Structure

• server/: Django gateway and management APIs
• runtime/: executor, bridge service, and runtime config
• frontend/: React + Vite frontend
• start_services.py: one-command local orchestrator

Quick Start

1. Set up Python environment

python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt

2. Install frontend dependencies

cd frontend
npm install

3. Initialize database

cd ../server
python manage.py migrate
python preset_tools.py

4. Return to project root and start all services

cd ..
python start_services.py

Default frontend URL: http://127.0.0.1:5173

Environment Variables

Copy .env.example to .env and configure as needed:

• DJANGO_SECRET_KEY
• DJANGO_DEBUG
• DJANGO_ALLOWED_HOSTS
• DJANGO_CORS_ALLOWED_ORIGINS

Notes

• Runtime config file: runtime/config.json
• MCP Bridge script: runtime/mcp_bridge.py