Picflow MCP server through Cotlet.dev

Connect Picflow to ChatGPT, Claude, Codex and Claude Code through Cotlet.dev. Create client galleries, summarize feedback and prepare replies in your own signed-in Picflow workspace.

This is an unofficial integration, not affiliated with Picflow. Cotlet.dev hosts the connection through your Cloud Browser. This repository provides an optional Python stdio MCP bridge.

Connect your account

1. Request access to Picflow.

2. Open https://app.picflow.com/ in your Cotlet.dev Cloud Browser, sign in yourself and enable Picflow for agents.

3. Connect your agent. Refresh the connector if you enabled Picflow after connecting.

ChatGPT

Open Settings > Apps & Connectors > Create. Enter https://cotlet.dev/mcp/v1/connect as the MCP server URL and choose OAuth.

Claude

Open Settings > Connectors > Add custom connector and enter https://cotlet.dev/mcp/v1/connect.

Codex

Create a Cotlet.dev API key in your console and set COTLET_API_KEY in your environment. Add:

[mcp_servers.cotlet]
url = "https://cotlet.dev/mcp/v1"
bearer_token_env_var = "COTLET_API_KEY"

Claude Code

claude mcp add --transport http cotlet https://cotlet.dev/mcp/v1 --header "Authorization: Bearer $COTLET_API_KEY"

Related MCP server: shootproof-mcp

Gallery and proofing workflows

Examples based on the live Picflow integration reference:

• Create a gallery from a Dropbox, Google Drive or Box folder.

• Summarize favorites, comments, annotations and approval flags.

• Draft replies to reviewers for approval before posting.

• Prepare retouch annotations and set asset statuses.

• Configure Approve-Only, an approval limit and download settings.

• Protect gallery access and organize delivered galleries into folders.

The live reference lists 13 capabilities, including 2 read and 11 write capabilities. The hosted groups are picflow_read and picflow_write. Operations:

• upload_assets

• import_from_cloud_storage

• manage_folders

• move_copy_gallery

• manage_gallery_sections

• manage_gallery_access

• get_share_links

• read_feedback

• reply_to_comment

• add_annotation

• set_asset_status

• configure_review_settings

• manage_team_members

get_share_links and read_feedback only read. Writes ask for confirmation by default; confirmation can be changed per tool. Review replies, access changes, invitations and deletions before execution. Deleting a folder deletes its galleries. Team writes require an owner or admin login. Features depend on your Picflow plan and permissions; first-time cloud storage authorization is completed by you in the Cloud Browser.

Optional local stdio bridge

Python 3.10 or newer is required, with no runtime dependencies. Clone this repository and configure a client that supports stdio:

{"mcpServers":{"picflow":{"command":"python3","args":["/absolute/path/to/picflow-mcp/picflow_agent.py"],"env":{"COTLET_API_KEY":"your-cotlet-key"}}}}

The local bridge lists seven browser helpers: picflow_guide, picflow_status, picflow_open, picflow_read, picflow_click, picflow_type and picflow_close. They forward to Cotlet.dev's shared browser tools and are distinct from the 13 hosted workflow capabilities. Call the guide first and close the browser when finished. Discovery works without a key; executing a tool requires your Cotlet.dev key and connected account.

python3 picflow_agent.py connect
python3 picflow_agent.py guide
python3 picflow_agent.py status
python3 picflow_agent.py serve

You can also build the included Dockerfile and pass COTLET_API_KEY as an environment variable.

Reference and access

• Picflow connection guide and operation reference

• Request access

• Cotlet.dev console

Licensed under Elastic License 2.0. See LICENSE.