MCP Image vs AI Vision MCP
A side-by-side look at the MCP Image and AI Vision MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose MCP Image for multimedia process work as a local process; choose AI Vision MCP for multimedia process as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose MCP Image when
- You need dedicated capabilities in the Multimedia Process domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
GEMINI_API_KEY, OPENAI_API_KEY, ARK_API_KEY, IMAGE_PROVIDER, IMAGE_OUTPUT_DIR, IMAGE_QUALITY, SKIP_PROMPT_ENHANCEMENT.
Choose AI Vision MCP when
- You need dedicated capabilities in the Multimedia Process domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
IMAGE_PROVIDER, VIDEO_PROVIDER, GEMINI_API_KEY, VERTEX_CLIENT_EMAIL, VERTEX_PRIVATE_KEY, VERTEX_PROJECT_ID, GCS_BUCKET_NAME. - You want tools like
analyze_image, compare_images, detect_objects_in_image.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Multimedia Process | Multimedia Process |
| Quality signal | 53/100 · Good | 63/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | API key required | API key required |
| Pricing | BYOK (pay the provider) | BYOK (pay the provider) |
| Required env vars | GEMINI_API_KEYOPENAI_API_KEYARK_API_KEYIMAGE_PROVIDERIMAGE_OUTPUT_DIRIMAGE_QUALITYSKIP_PROMPT_ENHANCEMENT | IMAGE_PROVIDERVIDEO_PROVIDERGEMINI_API_KEYVERTEX_CLIENT_EMAILVERTEX_PRIVATE_KEYVERTEX_PROJECT_IDGCS_BUCKET_NAME |
| Verified owner | Community listing | Community listing |
| GitHub stars | 181 | 80 |
| Directory activity | 2 views 0 installs 0 upvotes | 5 views 0 installs 0 upvotes |
| Tools | Not listed | 4 |
| Full listing | View MCP Image | View AI Vision MCP |
Tools & capabilities
MCP Image tools
No tool names declared yet. Check the project README from the listing page.
AI Vision MCP tools 4
analyze_imageAnalyze an image using AI vision models. Supports URLs, base64 data, and local file paths.compare_imagesCompare multiple images using AI vision models. Supports URLs, base64 data, and local file paths.detect_objects_in_imageDetect objects in an image using AI vision models and generate annotated images with bounding boxes. Supports URLs, base64 data, and local file paths. File handling: explicit filePath → exact path, otherwise → temp directory. Uses optimized default parameters for object detection.analyze_videoAnalyze a video using AI vision models. Supports URLs and local file paths.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
MCP Image
{
"mcpServers": {
"mcp-image": {
"command": "npx",
"args": [
"-y",
"mcp-image"
],
"env": {
"GEMINI_API_KEY": "YOUR_GEMINI_API_KEY_HERE",
"OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
"ARK_API_KEY": "YOUR_ARK_API_KEY_HERE",
"IMAGE_PROVIDER": "YOUR_IMAGE_PROVIDER_HERE",
"IMAGE_OUTPUT_DIR": "YOUR_IMAGE_OUTPUT_DIR_HERE",
"IMAGE_QUALITY": "YOUR_IMAGE_QUALITY_HERE",
"SKIP_PROMPT_ENHANCEMENT": "YOUR_SKIP_PROMPT_ENHANCEMENT_HERE"
}
}
}
}
AI Vision MCP
{
"mcpServers": {
"tan-yong-sheng-ai-vision-mcp": {
"command": "npx",
"args": [
"-y",
"ai-vision-mcp"
],
"env": {
"IMAGE_PROVIDER": "YOUR_IMAGE_PROVIDER_HERE",
"VIDEO_PROVIDER": "YOUR_VIDEO_PROVIDER_HERE",
"GEMINI_API_KEY": "YOUR_GEMINI_API_KEY_HERE",
"VERTEX_CLIENT_EMAIL": "YOUR_VERTEX_CLIENT_EMAIL_HERE",
"VERTEX_PRIVATE_KEY": "YOUR_VERTEX_PRIVATE_KEY_HERE",
"VERTEX_PROJECT_ID": "YOUR_VERTEX_PROJECT_ID_HERE",
"GCS_BUCKET_NAME": "YOUR_GCS_BUCKET_NAME_HERE"
}
}
}
}
Frequently asked questions
MCP Image is categorized under Multimedia Process and uses a local stdio subprocess. AI Vision MCP belongs to Multimedia Process and uses a local stdio subprocess. Pick MCP Image for multimedia process work and AI Vision MCP for multimedia process.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
MCP Image is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. AI Vision MCP is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add mcp-image and tan-yong-sheng-ai-vision-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, MCP Image has a quality signal of 53/100 (Good) with 2 views, 0 installs and 181 GitHub stars. AI Vision MCP has 63/100 (Good) with 5 views, 0 installs and 80 GitHub stars.