Validation
Validate Docker image names and tags according to Docker naming conventions
Call this tool from your code in three languages.
curl -X POST 'https://api.elysiatools.com/en/api/tools/docker-image-tag-validator' \
-H 'Content-Type: application/json' \
-d '{"imageRef":"Enter image reference (e.g., nginx:latest, docker.io/library/nginx:alpine)..."}'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/docker-image-tag-validator| Name | Type | Required | Description |
|---|---|---|---|
| imageRef | text | Yes | — |
Text result
{
"result": "Processed text content",
"error": "Error message (optional)",
"message": "Notification message (optional)",
"metadata": {
"key": "value"
}
}Add this tool to your Model Context Protocol server so AI agents can list and call it.
Add this block to your MCP client configuration:
{
"mcpServers": {
"elysiatools-docker-image-tag-validator": {
"name": "docker-image-tag-validator",
"description": "Validate Docker image names and tags according to Docker naming conventions",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=docker-image-tag-validator",
"command": "",
"args": [],
"env": {},
"isActive": true,
"type": "sse"
}
}
}After connecting to the SSE endpoint, list the exposed tools:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/list"
}Invoke the tool by its id, passing arguments built from its parameters:
{
"jsonrpc": "2.0",
"id": 2,
"method": "tools/call",
"params": {
"name": "docker-image-tag-validator",
"arguments": {
"imageRef": "Enter image reference (e.g., nginx:latest, docker.io/library/nginx:alpine)..."
}
}
}Questions or issues? Contact [email protected]