dcc-mcp-fpt
Bridges AI assistants to Autodesk ShotGrid (Flow Production Tracking) data, enabling CRUD, search, batch operations, and schema exploration via typed MCP tools with progressive loading.
README
dcc-mcp-fpt
ShotGrid (Flow Production Tracking) adapter for the DCC-MCP ecosystem.
Bridges AI assistants (Claude, Cursor, VS Code Copilot) to ShotGrid data through typed, progressively-loaded MCP tools built on dcc-mcp-core.
This is a fresh re-implementation of the shotgrid-mcp-server using the dcc-mcp framework — providing the same ShotGrid integration surface with gateway routing, skill-based progressive loading, and multi-DCC observability built in.
Why Use It
| Feature | Description |
|---|---|
| 20+ Typed Tools | CRUD, search, batch, notes, schema — all with validated schemas |
| Progressive Loading | Bootstrap tools eager-loaded; advanced tools loaded on demand |
| Gateway Ready | Plugs into the dcc-mcp gateway for unified multi-service routing |
| Skill-First | Every tool is a typed skill with tools.yaml, schemas, and annotations |
| Connection Pooling | Reuses authenticated sessions for performance |
| Schema Caching | Entity field schemas cached with configurable TTL |
| Multi-Transport | stdio, HTTP, and ASGI — works anywhere |
| Docker Ready | Single-command container deployment |
Quick Start
Install
pip install dcc-mcp-fpt
Or with uv:
uv pip install dcc-mcp-fpt
Configure
Set your ShotGrid credentials:
export SHOTGRID_URL="https://mysite.shotgrid.autodesk.com"
export SHOTGRID_SCRIPT_NAME="my_script_name"
export SHOTGRID_SCRIPT_KEY="my_script_key"
export SHOTGRID_PROJECT="my_project_code"
export SHOTGRID_PERMISSION_LEVEL="read"
Run Locally
The shortest local path is:
uvx dcc-mcp-fpt
By default this starts the adapter at http://127.0.0.1:8765/mcp and enables
the dcc-mcp gateway on http://127.0.0.1:9765/mcp. If a healthy gateway is
already running on that port, this FPT adapter registers into it; otherwise the
core gateway election path can own the gateway port for the local session.
Use standalone mode only when you do not want gateway registration:
uvx dcc-mcp-fpt --no-gateway
# Same as: uvx dcc-mcp-fpt --gateway-port 0
Development checkout:
python -m dcc_mcp_fpt
just serve-gateway
just serve-standalone
ASGI mode for uvicorn/gunicorn remains available:
uvicorn dcc_mcp_fpt.asgi:app --host 0.0.0.0 --port 8000
IDE MCP Config
For IDEs that support Streamable HTTP MCP, point the IDE at the gateway URL:
{
"mcpServers": {
"shotgrid": {
"url": "http://127.0.0.1:9765/mcp"
}
}
}
If your IDE only supports stdio MCP, use uvx directly:
{
"mcpServers": {
"shotgrid": {
"command": "uvx",
"args": ["dcc-mcp-fpt", "stdio", "--no-gateway"],
"env": {
"SHOTGRID_URL": "https://mysite.shotgrid.autodesk.com",
"SHOTGRID_SCRIPT_NAME": "my_script_name",
"SHOTGRID_SCRIPT_KEY": "my_script_key",
"SHOTGRID_PROJECT": "my_project_code",
"SHOTGRID_PERMISSION_LEVEL": "read"
}
}
}
}
mcpcall
After uvx dcc-mcp-fpt is running, smoke-test through the gateway:
mcpcall doctor --url http://127.0.0.1:9765/mcp --json
mcpcall list --url http://127.0.0.1:9765/mcp --json
mcpcall call --url http://127.0.0.1:9765/mcp shotgrid-discovery__check_connection
mcpcall call --url http://127.0.0.1:9765/mcp shotgrid-discovery__get_server_info
You can also import the same mcpServers JSON used by your IDE:
mcpcall config import --from ./mcp.json --output ./mcpcall.json
mcpcall list --config ./mcpcall.json --server shotgrid --json
Tool Surface
Bootstrap (eager-loaded)
| Skill | Tools |
|---|---|
shotgrid-discovery |
check_connection, list_entity_types, get_server_info |
shotgrid-setup |
generate_agent_config, validate_runtime_config |
shotgrid-schema |
get_schema, get_field_schema, list_entity_types |
Scene (loaded on demand)
| Skill | Tools |
|---|---|
shotgrid-crud |
find_entities, find_one_entity, create_entity, update_entity, delete_entity |
shotgrid-search |
search_entities, search_by_name |
Authoring
| Skill | Tools |
|---|---|
shotgrid-note |
create_note, find_notes, update_note |
Pipeline
| Skill | Tools |
|---|---|
shotgrid-batch |
batch_operations |
Architecture
AI Agent (Claude, Cursor, Copilot)
│
│ MCP Protocol (stdio / HTTP / ASGI)
▼
┌───────────────────────────────┐
│ ShotGridMcpServer │
│ (DccServerBase adapter) │
│ │
│ ┌─────────────────────────┐ │
│ │ Skill Catalog │ │
│ │ (progressive loading) │ │
│ └───────────┬─────────────┘ │
│ │ │
│ ┌───────────▼─────────────┐ │
│ │ HostExecutionBridge │ │
│ │ → ShotGridClient │ │
│ └───────────┬─────────────┘ │
│ │ │
│ ┌───────────▼─────────────┐ │
│ │ ConnectionPool │ │
│ │ SchemaCache │ │
│ └───────────┬─────────────┘ │
└──────────────┼────────────────┘
│
│ shotgun_api3 (REST)
▼
┌─────────────────┐
│ ShotGrid API │
│ (Autodesk FPT) │
└─────────────────┘
Configuration
| Variable | Required | Description |
|---|---|---|
SHOTGRID_URL |
Yes | ShotGrid server URL |
SHOTGRID_SCRIPT_NAME |
Yes | Script/API user name |
SHOTGRID_SCRIPT_KEY |
Yes | Script/API user key |
SHOTGRID_PROJECT |
No | Default project name, code, or tank name for scoped tools |
SHOTGRID_PROJECT_ID |
No | Default project ID; overrides SHOTGRID_PROJECT when set |
SHOTGRID_PERMISSION_LEVEL |
No | Fallback permission level: read, write, or admin |
SHOTGRID_PROJECT_PERMISSIONS |
No | JSON or CSV per-project permission allowlist |
SHOTGRID_READ_ONLY |
No | Set to 1 to block create/update/delete regardless of level |
DCC_MCP_GATEWAY_PORT |
No | dcc-mcp gateway port; set 0 to run standalone |
DCC_MCP_REGISTRY_DIR |
No | Shared gateway registry directory |
DCC_MCP_FPT_GATEWAY_SCENE |
No | Gateway context label; defaults to project:<SHOTGRID_PROJECT> |
DCC_MCP_FPT_GATEWAY_DISPLAY_NAME |
No | Human-readable label shown in gateway/admin surfaces |
DCC_MCP_FPT_ENABLE_GATEWAY_FAILOVER |
No | Set 0 to disable core gateway election/failover |
DCC_MCP_FPT_SKILL_PATHS |
No | FPT-specific custom skill roots (; on Windows, : on Unix) |
DCC_MCP_SKILL_PATHS |
No | Global custom skill roots shared by all dcc-mcp adapters |
DCC_MCP_SHOTGRID_MINIMAL |
No | Comma-separated minimal mode skill list |
DCC_MCP_SHOTGRID_DEFAULT_TOOLS |
No | Comma-separated default tools to activate |
Project Scoping and Permissions
CRUD and batch tools accept optional project, project_id, and
project_scoped inputs. When a default project is configured, reads add a
ShotGrid project filter, creates inject data.project when missing, and
updates/deletes validate project ownership before mutating data.
Permission levels are intentionally simple:
| Level | Allows |
|---|---|
read |
find, find_one, schema, connection checks |
write |
read plus create/update and non-delete batch items |
admin |
write plus delete/retire |
Examples:
export SHOTGRID_PROJECT="my_project_code"
export SHOTGRID_PERMISSION_LEVEL="write"
export SHOTGRID_PROJECT_PERMISSIONS='{"my_project_code":"write","id:456":"read"}'
Gateway Integration
The adapter uses the same DccServerOptions.from_env(...) gateway contract as
the Maya, Blender, Houdini, and 3ds Max adapters. When DCC_MCP_GATEWAY_PORT
or --gateway-port is set to a positive value, the server publishes an FPT
runtime entry with a safe display name, project-aware scene label, version, and
gateway election diagnostics.
export SHOTGRID_PROJECT="my_project_code"
export DCC_MCP_GATEWAY_PORT=9765
export DCC_MCP_FPT_GATEWAY_DISPLAY_NAME="FPT my_project_code"
just serve-gateway
Use --gateway-port 0 or just serve-standalone for local standalone testing.
The shotgrid-discovery__get_server_info tool includes a gateway diagnostics
object so agents and CI can confirm whether this instance joined the gateway.
Request-Scoped Credentials
HTTP MCP clients do not inject mcp.json.env into an already-running Gateway.
For shared Gateway deployments, keep ShotGrid secrets in adapter-side profiles
and pass request context through MCP _meta. With core PIP-520, caller identity
lives under _meta.agent_context, while credential and policy controls are
bounded top-level _meta fields:
{
"_meta": {
"agent_context": {
"requester_id": "hallong",
"requester_type": "human"
},
"credential_profile": "sg-read-zombie",
"permission_hint": "read",
"project_scope": "my_project_code"
}
}
Legacy clients that still send credential_profile, permission_hint, or
project_scope inside _meta.agent_context remain supported as a fallback, but
new agents should use the PIP-520 top-level _meta shape above.
Profiles can be supplied as JSON in DCC_MCP_FPT_CREDENTIAL_PROFILES or from a
JSON file via DCC_MCP_FPT_CREDENTIAL_PROFILES_FILE:
{
"sg-read-zombie": {
"url": "https://mysite.shotgrid.autodesk.com",
"script_name": "sg_read_bot",
"script_key": "<secret stored outside chat>",
"permission_level": "read",
"read_only": true,
"project": "my_project_code"
}
}
permission_hint can only reduce the effective policy. It is merged with the
env/profile policy by minimum permission, so an agent cannot turn a read profile
into write/admin. Inline credentials are rejected unless
DCC_MCP_ALLOW_INLINE_CREDENTIALS=1 is set for local development.
Agent Setup Skill
shotgrid-setup is eager-loaded so agents can bootstrap configuration without
guessing repo conventions:
mcpcall call --url http://127.0.0.1:9765/mcp shotgrid-setup__validate_runtime_config
mcpcall call --url http://127.0.0.1:9765/mcp shotgrid-setup__generate_agent_config target=all
The generated config includes uvx dcc-mcp-fpt, HTTP/stdio IDE snippets,
mcpcall commands, Docker examples, and custom skill path environment variables.
Secret values are redacted by default.
Custom Skills
Point DCC_MCP_FPT_SKILL_PATHS at a skill package directory or a parent
directory containing multiple skill package folders:
# Windows uses semicolon between multiple roots.
set DCC_MCP_FPT_SKILL_PATHS=C:\studio\fpt-skills;C:\show\fpt-skills
# Linux/macOS uses colon.
export DCC_MCP_FPT_SKILL_PATHS=/studio/fpt-skills:/show/fpt-skills
uvx dcc-mcp-fpt
Use DCC_MCP_SKILL_PATHS for shared cross-adapter skills. The gateway admin
skill path registry is also picked up by dcc-mcp-core on startup/reload.
Container Deployment
Build and run locally:
docker build -t dcc-mcp-fpt .
docker run --rm \
-p 8765:8765 \
-p 9765:9765 \
--env-file .env \
dcc-mcp-fpt
Inject custom skills by mounting a directory to /skills; the image sets
DCC_MCP_FPT_SKILL_PATHS=/skills by default:
docker run --rm \
-p 8765:8765 \
-p 9765:9765 \
--env-file .env \
-v /studio/fpt-skills:/skills:ro \
dcc-mcp-fpt
Minimal compose:
services:
dcc-mcp-fpt:
image: dcc-mcp-fpt
ports:
- "8765:8765"
- "9765:9765"
env_file:
- .env
volumes:
- /studio/fpt-skills:/skills:ro
Development
git clone https://github.com/dcc-mcp/dcc-mcp-fpt.git
cd dcc-mcp-fpt
# Install with dev deps
uv pip install -e ".[dev]"
# Run tests
pytest --cov=src/dcc_mcp_fpt --cov-report=term
# Lint
ruff check src/ tests/
# Format
ruff format src/ tests/
Local Live CRUD Smoke
Copy .env.example to .env, fill in local credentials, and keep the file
untracked. The dry-run command verifies configuration and skips mutations:
just install-dev
just live-crud-smoke-dry
To run a real local create/find/update/delete cycle against the configured project, set an admin-capable policy for that project and run:
export SHOTGRID_PERMISSION_LEVEL="admin"
export SHOTGRID_LIVE_CRUD_CONFIRM=1
just live-crud-smoke
The smoke creates a temporary entity, updates it, and retires it on cleanup.
CI/CD
CIruns Python 3.8-3.12 across Linux, Windows, and macOS.- Lint, format check, bundled skill metadata lint, CLI smoke, package build, and Docker build are separate gates.
Releaseuses release-please, builds wheel/sdist artifacts, publishes via PyPI Trusted Publishing, and attaches the dist files to the GitHub Release.Live ShotGrid Smokeis manual-only and uses GitHub Secrets; it defaults to dry-run behavior unless CRUD confirmation is enabled.
Requirements
- Python 3.8+
- dcc-mcp-core >= 0.17.54
- shotgun_api3 >= 3.4.0
License
MIT — see LICENSE.
Related
- dcc-mcp-core — Core runtime and shared tooling
- shotgrid-mcp-server — Original FastMCP-based implementation
- dcc-mcp-maya — Maya adapter reference
- dcc-mcp-blender — Blender adapter reference
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