About 🎯 ShotGrid MCP Server
An MCP server for Autodesk ShotGrid (Flow Production Tracking) that offers broad CRUD and batch data operations. It is aimed at production teams who track work in ShotGrid and want AI assistants to access that data directly.
Key features
- 0140+ tools covering CRUD operations
- 02Batch create, update and delete entities
- 03Thumbnail, note and playlist operations
- 04Supports stdio and HTTP transports
- 05Bundled interactive status dashboard MCP App
Use cases
- 01Finding shots updated in a project during the past week
- 02Batch creating assets and assigning tasks
- 03Summarising time logs and producing visual reports
MCP support
The project is an MCP server that exposes ShotGrid entities and operations as tools to MCP clients such as Claude Desktop, Cursor and VS Code, with optional remote HTTP access.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README
ShotGrid MCP Server
A Model Context Protocol (MCP) server that provides AI assistants with seamless access to Autodesk ShotGrid (Flow Production Tracking)
English | 简体中文
📖 Documentation | 中文文档
Overview
ShotGrid MCP Server enables AI assistants like Claude, Cursor, and VS Code Copilot to interact directly with your ShotGrid (Flow Production Tracking) data. Built on FastMCP, it provides a high-performance bridge between AI tools and production tracking workflows.
Demo
0. Configure ShotGrid MCP in Code Editor

1. Query Task Schedule & Workload Visualization

Prompt: Query the team's task schedule for the past week, calculate workload rate based on 8 hours per day, and visualize it in web format
2. Batch Create Assets & Assign Tasks

Prompt: Batch create the recommended hero characters in the shotgrid Demo:Animation project, categorize them as characters, use the FilmVFX-CharacterAsset task template, assign tasks to Yang Zhuo, with start and end dates set to next week
3. TimeLog Statistics & Visualization

Prompt: Query timelog data from shotgrid and visualize it in web format
4. Department Efficiency Statistics & Send to WeCom

Prompt: Calculate department efficiency and send the data to WeCom. Efficiency formula: Efficiency = Task bid / Timelog hours
More Examples

Features
| Category | Highlights |
|---|---|
| 40+ Tools | Complete CRUD operations, batch processing, thumbnails, notes, playlists |
| Transport | stdio (local), HTTP (remote), ASGI (production) |
| Performance | Connection pooling, schema caching, lazy initialization |
| Skills | Bundled Agent Skills over MCP (io.modelcontextprotocol/skills) |
| Deployment | FastMCP Cloud, Docker, uvicorn/gunicorn, any ASGI server |
| Platform | Windows, macOS, Linux |
Quick Start
Installation
# Using uv (recommended)
uv pip install shotgrid-mcp-server
# Or using pip
pip install shotgrid-mcp-server
Configuration
Set your ShotGrid credentials:
export SHOTGRID_URL="https://your-site.shotgunstudio.com"
export SHOTGRID_SCRIPT_NAME="your_script_name"
export SHOTGRID_SCRIPT_KEY="your_script_key"
Usage
stdio Transport (Default) - For Claude Desktop, Cursor, etc.
uvx shotgrid-mcp-server
HTTP Transport - For Remote Access
uvx shotgrid-mcp-server http --host 0.0.0.0 --port 8000
MCP Client Configuration
Add the server to your MCP client configuration:
Claude Desktop
{
"mcpServers": {
"shotgrid": {
"command": "uvx",
"args": ["shotgrid-mcp-server"],
"env": {
"SHOTGRID_URL": "https://your-site.shotgunstudio.com",
"SHOTGRID_SCRIPT_NAME": "your_script_name",
"SHOTGRID_SCRIPT_KEY": "your_script_key"
}
}
}
}
Cursor / VS Code / Other MCP Clients
{
"mcpServers": {
"shotgrid": {
"command": "uvx",
"args": ["shotgrid-mcp-server"],
"env": {
"SHOTGRID_URL": "https://your-site.shotgunstudio.com",
"SHOTGRID_SCRIPT_NAME": "your_script_name",
"SHOTGRID_SCRIPT_KEY": "your_script_key"
}
}
}
}
HTTP Transport (Remote)
{
"mcpServers": {
"shotgrid": {
"type": "http",
"url": "http://your-server:8000/mcp"
}
}
}
Deployment
| Method | Command / Setup |
|---|---|
| FastMCP Cloud | Deploy via fastmcp.cloud with fastmcp_entry.py |
| ASGI | uvicorn shotgrid_mcp_server.asgi:app --host 0.0.0.0 --port 8000 |
| Docker | See Deployment Guide |
See the Deployment Guide for detailed instructions.
Available Tools
This server provides 40+ tools for interacting with ShotGrid:
| Category | Tools |
|---|---|
| CRUD | create_entity, find_one_entity, search_entities, update_entity, delete_entity |
| Batch | batch_create, batch_update, batch_delete |
| Media | download_thumbnail, upload_thumbnail |
| Notes | shotgrid.note.create, shotgrid.note.read, shotgrid.note.update |
| Playlists | create_playlist, find_playlists |
| MCP Apps | shotgrid_dashboard (interactive status dashboard) |
| Direct API | sg.find, sg.create, sg.update, sg.batch, and more... |
MCP Apps
shotgrid_dashboard is an MCP App: it returns data and an interactive UI. The tool advertises ui://shotgrid/dashboard in its _meta.ui.resourceUri, and the host renders that resource in a sandboxed iframe.
Hosts without MCP Apps support automatically receive the same summary as plain text.
The UI is bundled into a single self-contained HTML file, so no Node runtime is needed in production. See the MCP Apps guide for the wire format and rebuild instructions.
python scripts/verify_mcp_app.py
Example Prompts
Once connected, you can ask your AI assistant:
- "Find all shots updated last week in Project X"
- "Create a playlist with yesterday's lighting renders"
- "Add a note to SHOT_010 about the background lighting"
- "Summarize time logs for the Animation department this month"
- "Show me a dashboard of Task statuses for Project X"
Development
# Clone and install
git clone https://github.com/loonghao/shotgrid-mcp-server.git
cd shotgrid-mcp-server
pip install -r requirements-dev.txt
# Run tests
nox -s tests
# Development server with hot reload
uv run fastmcp dev src/shotgrid_mcp_server/server.py:mcp
# Verify the Skills extension against a live HTTP server
uv run python scripts/verify_skills_extension.py
Documentation
See the /docs directory for detailed documentation.
Contributing
Contributions welcome! Please follow the Google Python Style Guide, write tests, and use Conventional Commits — commit messages drive versioning and the changelog. See RELEASE.md for how releases are cut.
License
Architecture
flowchart TB
subgraph Clients["🤖 MCP Clients"]
direction LR
CLAUDE["Claude Desktop"]
CURSOR["Cursor"]
VSCODE["VS Code"]
AI["Other AI"]
end
subgraph MCP["⚡ ShotGrid MCP Server"]
direction LR
TOOLS["40+ Tools"]
POOL["Connection Pool"]
SCHEMA["Schema Cache"]
end
subgraph ShotGrid["🎬 ShotGrid API"]
direction LR
P["Projects"]
S["Shots"]
A["Assets"]
T["Tasks"]
N["Notes"]
end
Clients -->|"MCP Protocol<br/>stdio / http"| MCP
MCP -->|"REST API"| ShotGrid
style Clients fill:#2ecc71,stroke:#27ae60,color:#fff
style MCP fill:#3498db,stroke:#2980b9,color:#fff
style ShotGrid fill:#e74c3c,stroke:#c0392b,color:#fff
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.