agenticorg-mcp-server

MCP (Model Context Protocol) server for AgenticOrg — expose every AgenticOrg AI agent and native tool to any MCP-compatible client (live counts: /api/v1/product-facts).

Quick Start

npm install -g agenticorg-mcp-server
AGENTICORG_API_KEY=your-key agenticorg-mcp

Or run directly with npx:

AGENTICORG_API_KEY=your-key npx agenticorg-mcp-server

Configure in ChatGPT / Claude Desktop / Cursor

Add to your MCP client configuration:

{
  "mcpServers": {
    "agenticorg": {
      "command": "npx",
      "args": ["agenticorg-mcp-server"],
      "env": {
        "AGENTICORG_API_KEY": "your-api-key"
      }
    }
  }
}

Config file paths by platform

| Client | macOS | Windows | |--------|-------|---------| | Claude Desktop | ~/Library/Application Support/Claude/claude_desktop_config.json | %APPDATA%\Claude\claude_desktop_config.json | | ChatGPT Desktop | Currently in beta — config path may change. Check OpenAI docs for the latest. | Currently in beta — config path may change. | | Cursor | .cursor/mcp.json in your project root | .cursor/mcp.json in your project root |

Available Tools

| Tool | Description | |------|-------------| | list_agents | List all AI agents, filter by domain | | run_agent | Run any agent (AP Processor, Recon, Payroll, etc.) | | get_agent_details | Get full agent config and capabilities | | create_agent_from_sop | Parse SOP text → create new agent | | deploy_agent | Deploy an agent configuration | | list_connectors | List all native connectors and status | | call_connector_tool | Call any connector tool | | list_mcp_tools | Discover all available tools | | discover_agents_a2a | A2A protocol agent discovery | | get_agent_card | Get the public A2A Agent Card |

Authentication

Set one of these environment variables:

• AGENTICORG_API_KEY — API key from your AgenticOrg dashboard (Settings → API Keys)
• AGENTICORG_GRANTEX_TOKEN — Grantex grant token for delegated agent access

Optional:

• AGENTICORG_BASE_URL — Custom base URL (default: https://app.agenticorg.ai)

Example: Run an Invoice Agent from ChatGPT

Once configured, you can say in ChatGPT:

"Use AgenticOrg to process invoice INV-2024-001 from Tata Consultancy"

ChatGPT will call the run_agent tool with:

{
  "agent_type": "ap_processor",
  "inputs": { "invoice_id": "INV-2024-001", "vendor": "Tata Consultancy" }
}

Example: Create an Agent from SOP via ChatGPT

You can create a new agent directly from a standard operating procedure:

"Use AgenticOrg to create an agent from this SOP: Step 1 — Receive vendor invoice. Step 2 — Validate GSTIN. Step 3 — 3-way match with PO and GRN. Step 4 — If amount > 5L, escalate to CFO."

ChatGPT will call the create_agent_from_sop tool with:

{
  "sop_text": "Step 1: Receive vendor invoice\nStep 2: Validate GSTIN on GST portal\nStep 3: 3-way match with PO and GRN\nStep 4: If amount > 5L, escalate to CFO",
  "domain": "finance"
}

The server parses the SOP, generates an agent configuration, and returns the draft for review before deployment.

Troubleshooting

"AGENTICORG_API_KEY not set" error Make sure the env block in your MCP config includes the key, or export it in your shell before running:

export AGENTICORG_API_KEY=your-api-key

"Connection refused" or server not starting

• Verify Node.js >= 18 is installed: node --version
• Try running manually first: AGENTICORG_API_KEY=your-key npx agenticorg-mcp-server
• Check that no firewall or proxy is blocking local stdio communication

"Tool not found" when calling a connector tool

• Run list_mcp_tools first to see all available tool names
• Tool names follow the format connector_name:action (e.g., oracle_fusion:read:purchase_order)

Claude Desktop / Cursor not detecting the server

• Ensure the config JSON is valid (no trailing commas)
• Restart the client after editing the config file
• Check the client's MCP log for error messages

License

Apache-2.0