@asoc/mcp

MCP (Model Context Protocol) audit server for agent discovery and certification.

Installation

NPM Package

npm install -g @asoc/mcp

Add to MCP Clients

Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "asoc": {
      "command": "npx",
      "args": ["-y", "@asoc/mcp"]
    }
  }
}

Cursor

1. Open Cursor Settings
2. Go to Features → Model Context Protocol
3. Add new server:
   • Name: A-SOC Trust
   • Command: npx
   • Args: -y @asoc/mcp

Cline (VSCode Extension)

Edit ~/.cline/mcp.json:

{
  "mcpServers": {
    "asoc": {
      "command": "npx",
      "args": ["-y", "@asoc/mcp"]
    }
  }
}

Continue (VSCode Extension)

Edit ~/.continue/config.json:

{
  "experimental": {
    "modelContextProtocolServers": [
      {
        "name": "asoc",
        "command": "npx",
        "args": ["-y", "@asoc/mcp"]
      }
    ]
  }
}

Quick Start

Run Standalone Server

# Development mode
cd packages/mcp-server
npm run dev

# Production mode
ASOC_SECRET_KEY=your-secret npm start

Integrate with Your Application

import { createAsocMcpServer } from '@asoc/mcp';
import { TicketIssuer } from '@asoc/sdk';

const issuer = new TicketIssuer({
  signingKey: process.env.ASOC_SECRET_KEY!,
  issuer: 'asoc-authority.com',
});

const mcpServer = createAsocMcpServer(issuer);
// Connect your transport (HTTP, stdio, WebSocket, etc.)

Available Tools

1. is_agent_certified

Quick boolean check for agent certification status.

Input:

{
  "agentId": "agent-12345"
}

Output:

{
  "certified": true,
  "agentId": "agent-12345",
  "auditLevel": "Gold",
  "expiresAt": 1767890123,
  "killSwitchActive": false
}

2. get_trust_score

Calculate comprehensive trust score with behavioral factors.

Input:

{
  "agentId": "agent-12345",
  "includeHealth": true
}

Output:

{
  "agentId": "agent-12345",
  "score": 85,
  "level": "Gold",
  "factors": {
    "certification": 100,
    "behavioral_health": 92,
    "transaction_history": 77,
    "domain_verification": 100
  },
  "recommendation": "approve",
  "details": {
    "uptime_percentage": 99.8,
    "avg_latency_ms": 120,
    "error_rate": 0.002,
    "total_transactions": 15420,
    "last_active": 1734567890
  }
}

3. issue_audit_ticket

Generate signed JWT ticket for x402 transactions.

Input:

{
  "agentId": "agent-12345",
  "validitySeconds": 300
}

Output:

{
  "success": true,
  "ticket": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
  "agentId": "agent-12345",
  "expiresIn": 300
}

4. query_agents

Search for agents by criteria.

Input:

{
  "minTrustScore": 70,
  "auditLevel": "Gold",
  "capabilities": ["trading"],
  "limit": 5
}

Output:

{
  "results": [
    {
      "agentId": "agent-12345",
      "organization": "Acme AI Corp",
      "auditLevel": "Gold",
      "trustScore": 85,
      "capabilities": ["trading", "portfolio-analysis"]
    }
  ],
  "total": 1
}

5. activate_kill_switch

Emergency disable an agent.

Input:

{
  "agentId": "agent-12345",
  "reason": "Suspicious activity detected",
  "revokeTickets": true
}

Output:

{
  "success": true,
  "agentId": "agent-12345",
  "timestamp": 1734567890,
  "reason": "Suspicious activity detected"
}

MCP Client Integration

Using MCP TypeScript SDK

import { Client } from '@modelcontextprotocol/sdk/client/index.js';
import { HttpClientTransport } from '@modelcontextprotocol/sdk/client/http.js';

const client = new Client({
  name: 'my-agent',
  version: '1.0.0',
});

const transport = new HttpClientTransport('http://localhost:3100/mcp');
await client.connect(transport);

// Check if agent is certified
const result = await client.callTool({
  name: 'is_agent_certified',
  arguments: { agentId: 'agent-12345' },
});

console.log(result.content[0].text);

Using cURL

# Check certification
curl -X POST http://localhost:3100/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "is_agent_certified",
      "arguments": {
        "agentId": "agent-12345"
      }
    }
  }'

Environment Variables

Architecture

┌─────────────────────────────────────────────────────────┐
│                    MCP Client                           │
│              (Claude, GPT, Custom Agent)                │
└────────────────────┬────────────────────────────────────┘
                     │
                     │ MCP Protocol
                     │
┌────────────────────▼────────────────────────────────────┐
│              A-SOC MCP Server                           │
│  ┌─────────────────────────────────────────────────┐   │
│  │  Tools:                                         │   │
│  │  • is_agent_certified                           │   │
│  │  • get_trust_score                              │   │
│  │  • issue_audit_ticket                           │   │
│  │  • query_agents                                 │   │
│  │  • activate_kill_switch                         │   │
│  └─────────────────────────────────────────────────┘   │
└────────────────────┬────────────────────────────────────┘
                     │
                     ▼
           ┌─────────────────────┐
           │  Agent Registry     │
           │  (In-Memory / DB)   │
           └─────────────────────┘

Production Considerations

1. Replace In-Memory Registry: Use PostgreSQL/Redis for persistence
2. Add Authentication: Protect MCP endpoints with API keys
3. Enable Rate Limiting: Prevent abuse of certificate issuance
4. Implement Caching: Cache trust scores for 1-5 minutes
5. Add Monitoring: Track tool usage and latency
6. Use Secure Keys: Rotate ASOC_SECRET_KEY regularly
7. Enable HTTPS: Use TLS in production environments

Demo Data

The server ships with 2 demo agents:

• agent-12345: Gold tier, high trust score (85)
• agent-67890: Silver tier, moderate trust score (68)

Replace seedDemoAgents() in index.ts with your database integration.

Next Steps

1. Build custom agent registry backend
2. Integrate with x402 payment gateways
3. Add webhooks for kill switch notifications
4. Implement behavioral scoring ML model
5. Create agent onboarding dashboard