MCP Hub REST API

API Endpoints

Code Examples

# List all available MCP servers
curl -X GET https://api.mcphub.rest/v1/servers \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json"

# Create and execute an AI agent
curl -X POST https://api.mcphub.rest/v1/agents \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "customer-support-agent",
    "model": "gpt-4",
    "serverIds": ["srv_123", "srv_456"],
    "config": {
      "temperature": 0.7,
      "maxTokens": 2000
    }
  }'

// List all MCP servers and create an agent
const listServers = async () => {
  const response = await fetch('https://api.mcphub.rest/v1/servers', {
    method: 'GET',
    headers: {
      'Authorization': 'Bearer YOUR_API_TOKEN',
      'Content-Type': 'application/json'
    }
  });
  return await response.json();
};

// Execute an AI agent workflow
const executeAgent = async (agentId, input) => {
  const response = await fetch(`https://api.mcphub.rest/v1/agents/${agentId}/execute`, {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer YOUR_API_TOKEN',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      input: input,
      context: {
        userId: 'user_123',
        sessionId: 'session_456'
      }
    })
  });
  return await response.json();
};

import requests

# Configuration
API_TOKEN = 'YOUR_API_TOKEN'
BASE_URL = 'https://api.mcphub.rest/v1'
headers = {
    'Authorization': f'Bearer {API_TOKEN}',
    'Content-Type': 'application/json'
}

# List all MCP servers
response = requests.get(f'{BASE_URL}/servers', headers=headers)
servers = response.json()

# Create an AI agent
agent_data = {
    'name': 'data-analyst-agent',
    'model': 'gpt-4',
    'serverIds': ['srv_123', 'srv_456'],
    'config': {
        'temperature': 0.7,
        'maxTokens': 2000
    }
}
response = requests.post(f'{BASE_URL}/agents', headers=headers, json=agent_data)
agent = response.json()

# Execute the agent
execution_data = {
    'input': 'Analyze customer feedback from last month',
    'context': {'userId': 'user_123'}
}
response = requests.post(
    f'{BASE_URL}/agents/{agent["id"]}/execute',
    headers=headers,
    json=execution_data
)
result = response.json()

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