AI Tools
Solve math problems from images using AI vision models with step-by-step explanations
Call this tool from your code in three languages.
# 1) Upload each file first → returns { filePath }
curl -X POST 'https://api.elysiatools.com/upload/ai-math-solver' \
-F 'file=@/path/to/imageFile.ext'
# 2) Call the tool with the returned filePath values
curl -X POST 'https://api.elysiatools.com/en/api/tools/ai-math-solver' \
-F 'imageFile=/path/to/file.ext' \
-F 'outputLanguage=zh'Send a POST request with your inputs as JSON. File parameters require a separate upload first.
POST https://api.elysiatools.com/en/api/tools/ai-math-solver| Name | Type | Required | Description |
|---|---|---|---|
| imageFile | fileupload required | Yes | Supports JPG, PNG, WebP and other common image formats |
| outputLanguage | select | No | 选择解答结果的语言 |
Stream result
data: {"chunk": "data: processed content 1", "type": "stream"}
data: {"chunk": "data: processed content 2", "type": "stream"}
data: {"type": "done"}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-ai-math-solver": {
"name": "ai-math-solver",
"description": "Solve math problems from images using AI vision models with step-by-step explanations",
"baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=ai-math-solver",
"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": "ai-math-solver",
"arguments": {
"imageFile": "https://example.com/file.ext",
"outputLanguage": "zh"
}
}
}Questions or issues? Contact [email protected]