| name | stitch-upload-to-stitch |
| description | Upload local assets (images, mockups, extracted HTML, design markdown) to a Stitch project. ALWAYS use this skill when you need to upload visual assets, HTML pages, or design docs to Stitch, particularly when direct MCP tool calls fail or truncate due to base64 token limits. |
| allowed-tools | ["stitch*:*","Bash","Read","Write","web_fetch"] |
Upload-to-Stitch
Upload local assets (images, mockups, HTML, and markdown files) to a Stitch project using the
provided upload script, which bypasses the MCP tool's base64 output token limits.
[!NOTE]
The AI model cannot upload files via MCP tools directly because the base64
encoding of even a small file exceeds the model's output token limit (~16K
tokens). This script reads the file and sends it directly over HTTP.
Steps
1. Identify Target Project
Use list_projects to find the correct projectId.
2. Get the API Key
Locate your active MCP server configuration file and extract the API key:
- Antigravity:
.gemini/antigravity/mcp_config.json or .gemini/jetski/mcp_config.json
- Gemini CLI:
~/.gemini/settings.json or ~/.gemini/extensions/Stitch/gemini-extension.json
- Claude Code:
~/.claude.json
Extract:
- API Key: From the
X-Goog-Api-Key header or auth argument
- MCP URL (optional): From the
httpUrl or endpoint argument (defaults to
https://stitch.googleapis.com)
[!IMPORTANT]
If you cannot find the API key in any of these locations, or if you cannot access these files, you MUST ask the user to provide the Stitch API key. Do not proceed without a valid API key.
3. Run Upload Script
[!WARNING]
Checkpoint — User Confirmation Required.
Before running the upload script, you MUST pause and present the file(s)
to be uploaded (paths, sizes, and types) to the user and wait for explicit
approval. Do NOT execute the upload script until the user confirms.
Use run_command to execute the Python script:
python3 <SKILL_DIR>/scripts/upload_to_stitch.py \
--project-id <PROJECT_ID> \
--file-path <PATH_TO_FILE> \
--api-key <API_KEY> \
[--api-url <STITCH_API_URL>] \
[--title <SCREEN_TITLE>] \
[--generated-by <GENERATED_BY>]
[!TIP]
macOS / SSL Certificate Troubleshooting:
If the upload fails with ssl.SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] unable to get local issuer certificate, this means your Python installation does not have root certificate authorities configured.
The script automatically attempts to use the certifi package to load the CA bundle if it is installed in your python environment. If certifi is not installed, you can either install it (pip install certifi) or manually supply the SSL_CERT_FILE environment variable when running the script:
SSL_CERT_FILE=$(python3 -c "import certifi; print(certifi.where())") python3 <SKILL_DIR>/scripts/upload_to_stitch.py \
--project-id <PROJECT_ID> \
--file-path <PATH_TO_FILE> \
--api-key <API_KEY> \
[--api-url <STITCH_API_URL>] \
[--title <SCREEN_TITLE>] \
[--generated-by <GENERATED_BY>]
Supported File Types
| Extension | MIME Type |
|---|
.png | image/png |
.jpg, .jpeg | image/jpeg |
.webp | image/webp |
.html, .htm | text/html |
.md | text/markdown |
The script auto-detects MIME type from the file extension.
Script Options
--project-id: Required. The Stitch project ID.--file-path: Required. Path to the local file to upload.--api-key: Required. API key for Stitch authorization.--api-url: Optional. Base URL of the Stitch API. Defaults to https://stitch.googleapis.com.--title: Optional. Title for the uploaded screen.--generated-by: Optional. Specify how the uploaded file was generated (e.g., 'stitch::extract-static-html' skill, 'Claude Code', 'Codex', 'Gemini' etc.).
