MCP Tools Integration
Connect Inigami's processing capabilities directly to AI assistants like Claude through the Model Context Protocol.
What is MCP?
The Model Context Protocol (MCP) is a standard for connecting AI assistants to external tools and data sources. Inigami implements an MCP server that exposes all 20+ processing capabilities as tools that AI models can invoke directly.
This means an AI assistant like Claude can analyze images, process text, run object detection, and perform transforms -- all by calling Inigami tools through MCP without any custom integration code.
Configuration
Add Inigami to your MCP client configuration:
1{
2 "mcpServers": {
3 "inigami": {
4 "command": "inigami-mcp-server",
5 "args": ["--host", "localhost", "--port", "10210"],
6 "env": {}
7 }
8 }
9}Available MCP Tools
detect_objects
Run YOLOv5 object detection on an image and return structured bounding box results.
estimate_depth
Generate a monocular depth map from a single image using Sobel gradient analysis.
segment_image
Segment an image into K distinct regions using K-means clustering in LAB color space.
resize_image
Resize an image to specified dimensions with configurable interpolation method.
apply_filter
Apply color filters and adjustments including brightness, contrast, and saturation.
analyze_text
Perform text analysis including word count, spell check, and readability scoring.
analyze_sentiment
Classify text sentiment with confidence scoring and word-level breakdown.
extract_entities
Extract named entities (persons, organizations, locations, dates) from text.
detect_language
Identify the language of input text with confidence scoring and alternatives.
How It Works in Practice
When an AI assistant needs to process media, it calls Inigami tools through MCP:
// AI assistant uses the detect_objects tool
Tool: detect_objects
Input: { "image_path": "/data/photo.jpg" }
// Inigami MCP server translates to TCP JSON request
{
"request_id": "mcp-auto-001",
"type": "detect_objects",
"image_path": "/data/photo.jpg"
}
// Results returned to the AI assistant
Found 3 objects:
- person (95% confidence) at [120, 80, 200, 350]
- car (88% confidence) at [400, 200, 300, 180]
- bicycle (76% confidence) at [50, 300, 120, 100] Zero Integration Code
MCP handles the protocol translation. No custom API clients or SDKs needed.
AI-Native
AI assistants can reason about which tools to use and chain operations intelligently.
Same Performance
MCP tools use the same C++ processing engine. No performance overhead from the protocol layer.
Connect AI to Computer Vision
Give your AI assistant the power to see and process media with Inigami MCP tools.
Setup MCP Integration