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AI-Powered Cargo Management API

AI Operations

Endpoint

Download schema

AI-powered cargo management and optimization endpoints

Universal MCP endpoint

MCP Endpoint

Copy the url to connect any MCP-compatible AI tool

https://api.cosmocargo.space/ai/v1/mcp

AI Tool Configuration

Choose your AI tool and copy the configuration to get started.

Open Claude Desktop and click Settings in the lower corner
Navigate to Developer tab → Edit Config

Add this configuration to claude_desktop_config.json:

claude_desktop_config.json

{
  "mcpServers": {
    "Cosmo Cargo AI": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://api.cosmocargo.space/ai/v1/mcp"
      ]
    }
  }
}

Save the file and restart Claude Desktop. Look for the 🔨 icon in the bottom-right corner.

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

View official docs

Optimize cargo routing

POST

https://api.cosmocargo.space/ai/v1

/optimize

Uses advanced AI algorithms to find the optimal route for cargo shipments across the solar system, considering factors like transit time, cost, and special cargo requirements.

Optimize cargo routing › Request Body

origin

string · required

Origin space station or planet

Example: Earth Station Alpha

destination

string · required

Destination space station or planet

Example: Mars Colony Beta

object[] · required

object

Optimize cargo routing › Responses

200

Optimization completed successfully

object

estimatedCost

number · float

Cost in Galactic Credits

estimatedTime

integer

Transit time in Earth days

confidenceScore

number · float · min: 0 · max: 1

alternativeRoutes

array · SpaceRoute (circular)

POST/optimize

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    origin: 'Earth Station Alpha',
    destination: 'Mars Colony Beta',
    cargo: [{type: 'PERISHABLE', weight: 0, volume: 0, specialRequirements: ['string']}],
    constraints: {maxTransitTime: 0, preferredCarriers: ['string'], avoidRoutes: ['string']}
  })
};

fetch('https://api.cosmocargo.space/ai/v1/optimize', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Request Body

{
  "origin": "Earth Station Alpha",
  "destination": "Mars Colony Beta",
  "cargo": [
    {
      "type": "PERISHABLE",
      "weight": 0,
      "volume": 0,
      "specialRequirements": [
        "string"
      ]
    }
  ],
  "constraints": {
    "maxTransitTime": 0,
    "preferredCarriers": [
      "string"
    ],
    "avoidRoutes": [
      "string"
    ]
  }
}

json

Example Responses

{
  "recommendedRoute": {
    "routeId": "00000000-0000-0000-0000-000000000000",
    "waypoints": [
      "string"
    ],
    "carrier": "carrier",
    "vesselType": "FREIGHTER"
  },
  "estimatedCost": 0,
  "estimatedTime": 0,
  "confidenceScore": 0,
  "alternativeRoutes": [
    null
  ]
}

json

application/json

Predict shipment issues

POST

https://api.cosmocargo.space/ai/v1

/predict

Uses machine learning to predict potential issues with shipments including delays, damage risks, and route disruptions based on historical data and current space weather conditions.

Predict shipment issues › Request Body

shipmentId

string · uuid · required

predictionTypes

string[]

Enum values:

DELAY

DAMAGE

ROUTE_DISRUPTION

COST_OVERRUN

Predict shipment issues › Responses

200

Predictions generated successfully

object[]

overallRiskLevel

string · enum

Enum values:

LOW

MEDIUM

HIGH

CRITICAL

POST/predict

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({shipmentId: '00000000-0000-0000-0000-000000000000', predictionTypes: ['DELAY']})
};

fetch('https://api.cosmocargo.space/ai/v1/predict', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Request Body

{
  "shipmentId": "00000000-0000-0000-0000-000000000000",
  "predictionTypes": [
    "DELAY"
  ]
}

json

Example Responses

{
  "predictions": [
    {
      "type": "type",
      "probability": 0,
      "impact": "MINIMAL",
      "mitigation": "mitigation"
    }
  ],
  "overallRiskLevel": "LOW"
}

json

application/json

Analyze fleet performance

GET

https://api.cosmocargo.space/ai/v1

/analyze/fleet-performance

Provides AI-powered analytics on fleet performance including fuel efficiency, delivery times, and maintenance predictions.

Analyze fleet performance › query Parameters

timeRange

string · enum

Enum values:

30d

90d

Default: 30d

fleetId

string

Analyze fleet performance › Responses

200

Fleet analysis completed

overallScore

number · float · min: 0 · max: 100

object[]

GET/analyze/fleet-performance

const options = {method: 'GET'};

fetch('https://api.cosmocargo.space/ai/v1/analyze/fleet-performance', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Responses

{
  "overallScore": 0,
  "insights": [
    {
      "category": "category",
      "finding": "finding",
      "recommendation": "recommendation",
      "priority": "LOW"
    }
  ]
}

json

application/json

Quantum Transport

AI-Powered Cargo Management API

AI Operations

Endpoint

Download schema

AI-powered cargo management and optimization endpoints

Universal MCP endpoint

MCP Endpoint

Copy the url to connect any MCP-compatible AI tool

https://api.cosmocargo.space/ai/v1/mcp

AI Tool Configuration

Choose your AI tool and copy the configuration to get started.

Open Claude Desktop and click Settings in the lower corner
Navigate to Developer tab → Edit Config

Add this configuration to claude_desktop_config.json:

claude_desktop_config.json

{
  "mcpServers": {
    "Cosmo Cargo AI": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://api.cosmocargo.space/ai/v1/mcp"
      ]
    }
  }
}

Save the file and restart Claude Desktop. Look for the 🔨 icon in the bottom-right corner.

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

View official docs

Optimize cargo routing

POST

https://api.cosmocargo.space/ai/v1

/optimize

Uses advanced AI algorithms to find the optimal route for cargo shipments across the solar system, considering factors like transit time, cost, and special cargo requirements.

Optimize cargo routing › Request Body

origin

string · required

Origin space station or planet

Example: Earth Station Alpha

destination

string · required

Destination space station or planet

Example: Mars Colony Beta

object[] · required

object

Optimize cargo routing › Responses

200

Optimization completed successfully

object

estimatedCost

number · float

Cost in Galactic Credits

estimatedTime

integer

Transit time in Earth days

confidenceScore

number · float · min: 0 · max: 1

alternativeRoutes

array · SpaceRoute (circular)

POST/optimize

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    origin: 'Earth Station Alpha',
    destination: 'Mars Colony Beta',
    cargo: [{type: 'PERISHABLE', weight: 0, volume: 0, specialRequirements: ['string']}],
    constraints: {maxTransitTime: 0, preferredCarriers: ['string'], avoidRoutes: ['string']}
  })
};

fetch('https://api.cosmocargo.space/ai/v1/optimize', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Request Body

{
  "origin": "Earth Station Alpha",
  "destination": "Mars Colony Beta",
  "cargo": [
    {
      "type": "PERISHABLE",
      "weight": 0,
      "volume": 0,
      "specialRequirements": [
        "string"
      ]
    }
  ],
  "constraints": {
    "maxTransitTime": 0,
    "preferredCarriers": [
      "string"
    ],
    "avoidRoutes": [
      "string"
    ]
  }
}

json

Example Responses

{
  "recommendedRoute": {
    "routeId": "00000000-0000-0000-0000-000000000000",
    "waypoints": [
      "string"
    ],
    "carrier": "carrier",
    "vesselType": "FREIGHTER"
  },
  "estimatedCost": 0,
  "estimatedTime": 0,
  "confidenceScore": 0,
  "alternativeRoutes": [
    null
  ]
}

json

application/json

Predict shipment issues

POST

https://api.cosmocargo.space/ai/v1

/predict

Uses machine learning to predict potential issues with shipments including delays, damage risks, and route disruptions based on historical data and current space weather conditions.

Predict shipment issues › Request Body

shipmentId

string · uuid · required

predictionTypes

string[]

Enum values:

DELAY

DAMAGE

ROUTE_DISRUPTION

COST_OVERRUN

Predict shipment issues › Responses

200

Predictions generated successfully

object[]

overallRiskLevel

string · enum

Enum values:

LOW

MEDIUM

HIGH

CRITICAL

POST/predict

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({shipmentId: '00000000-0000-0000-0000-000000000000', predictionTypes: ['DELAY']})
};

fetch('https://api.cosmocargo.space/ai/v1/predict', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Request Body

{
  "shipmentId": "00000000-0000-0000-0000-000000000000",
  "predictionTypes": [
    "DELAY"
  ]
}

json

Example Responses

{
  "predictions": [
    {
      "type": "type",
      "probability": 0,
      "impact": "MINIMAL",
      "mitigation": "mitigation"
    }
  ],
  "overallRiskLevel": "LOW"
}

json

application/json

Analyze fleet performance

GET

https://api.cosmocargo.space/ai/v1

/analyze/fleet-performance

Provides AI-powered analytics on fleet performance including fuel efficiency, delivery times, and maintenance predictions.

Analyze fleet performance › query Parameters

timeRange

string · enum

Enum values:

30d

90d

Default: 30d

fleetId

string

Analyze fleet performance › Responses

200

Fleet analysis completed

overallScore

number · float · min: 0 · max: 100

object[]

GET/analyze/fleet-performance

const options = {method: 'GET'};

fetch('https://api.cosmocargo.space/ai/v1/analyze/fleet-performance', options)
  .then(response => response.json())
  .then(response => console.log(response))
  .catch(err => console.error(err));

Example Responses

{
  "overallScore": 0,
  "insights": [
    {
      "category": "category",
      "finding": "finding",
      "recommendation": "recommendation",
      "priority": "LOW"
    }
  ]
}

json

application/json

Quantum Transport