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# requires-python = ">=3.10"
# dependencies = ["mcp>=1.0", "openai>=1.0", "requests>=2.31"]
# ///
import os
import base64
import tempfile
import requests
from urllib.parse import urlparse
from mcp.server.fastmcp import FastMCP
from openai import OpenAI
mcp = FastMCP("Robust-Vision-Server")
def is_valid_url(url: str) -> bool:
"""Return True iff the input is a syntactically valid http/https URL."""
try:
result = urlparse(url)
return all([result.scheme in ['http', 'https'], result.netloc])
except ValueError:
return False
def get_base64_from_local_file(file_path: str) -> str:
"""Read a local image file and encode it as a base64 data URI."""
if not os.path.exists(file_path):
raise FileNotFoundError(f"local file not found: {file_path}")
with open(file_path, "rb") as f:
encoded = base64.b64encode(f.read()).decode('utf-8')
# OpenRouter accepts a generic image/jpeg URI; the API infers the real format.
return f"data:image/jpeg;base64,{encoded}"
@mcp.tool()
def analyze_image_with_openrouter(
image_source: str,
prompt: str = "Describe the image in detail and extract any salient text or information.",
model_name: str = "bytedance-seed/seed-2.0-lite",
) -> str:
"""
Analyze an image with an OpenRouter vision model. Accepts both local file
paths and remote http/https URLs. Remote images are downloaded to a
temporary directory before being sent to the API.
Args:
image_source: absolute local path or http/https URL.
prompt: instruction passed to the vision model.
model_name: OpenRouter model id.
"""
api_key = os.getenv("OPENROUTER_API_KEY")
if not api_key:
return "Error: OPENROUTER_API_KEY is not set."
client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=api_key)
# Branch A: remote URL — download to a temp dir, then call the API.
if is_valid_url(image_source):
with tempfile.TemporaryDirectory() as temp_dir:
temp_file_path = os.path.join(temp_dir, "downloaded_image.tmp")
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
"Accept": "image/webp,image/apng,image/*,*/*;q=0.8",
}
response = requests.get(image_source, headers=headers, stream=True, timeout=15)
response.raise_for_status()
content_type = response.headers.get('Content-Type', '')
if not content_type.startswith('image/'):
return f"Download failed: target URL did not return an image (Content-Type: {content_type})."
with open(temp_file_path, 'wb') as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
image_data_uri = get_base64_from_local_file(temp_file_path)
except requests.exceptions.Timeout:
return "Download failed: request timed out (>15s)."
except requests.exceptions.HTTPError as err:
return f"Download failed: HTTP error {err.response.status_code}."
except requests.exceptions.RequestException as err:
return f"Download failed: network error: {err}"
except Exception as err:
return f"Temp-file processing failed: {err}"
# Call inside the `with` block so the temp file outlives the request.
return _call_openrouter_api(client, model_name, prompt, image_data_uri)
# Branch B: local file path.
try:
image_data_uri = get_base64_from_local_file(image_source)
return _call_openrouter_api(client, model_name, prompt, image_data_uri)
except Exception as err:
return f"Local file processing failed: {err}"
def _call_openrouter_api(client: OpenAI, model: str, prompt: str, image_data_uri: str) -> str:
try:
response = client.chat.completions.create(
model=model,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": prompt},
{"type": "image_url", "image_url": {"url": image_data_uri}},
],
}
],
)
return response.choices[0].message.content
except Exception as err:
return f"OpenRouter API call failed: {err}"
if __name__ == "__main__":
mcp.run()
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