MCP Integration

JAOT exposes its optimization capabilities through the Model Context Protocol (MCP), allowing AI agents and LLM-powered applications to discover and use optimization tools without custom integration code.

What is MCP?

The Model Context Protocol is an open standard that lets AI applications discover and call external tools. Instead of writing bespoke API integrations, an MCP client (such as Claude Desktop, Cursor, or any compatible agent) connects to an MCP server and automatically discovers the tools it provides.

For JAOT, this means any MCP-compatible AI assistant can:

• Solve optimization problems by describing them in conversation
• Browse the template library and marketplace
• Execute activated models with user data
• Check credit balances and execution results

Connecting to JAOT via MCP

JAOT runs an MCP server at the /mcp endpoint using HTTP (Streamable HTTP) transport.

Endpoint:

https://jaot.io/mcp

The MCP endpoint is publicly accessible — no authentication is needed to connect and discover tools. Individual tools that modify data or consume credits require a Bearer API key, which is passed as a header on tool invocations.

Self-hosters: replace https://jaot.io/mcp with http://localhost:8001/mcp or your own domain.

Client setup

Claude Code (CLI)

Use claude mcp add with the --transport http flag:

claude mcp add --transport http jaot https://jaot.io/mcp \
  --header "Authorization: Bearer ok_live_your_key_here"

To browse templates and the marketplace without authenticating, omit the --header flag — those tools work without a key.

Claude Desktop

Claude Desktop does not support remote HTTP servers via claude_desktop_config.json directly. Add JAOT through the Settings → Connectors UI at claude.ai/settings/connectors:

1. Click Add custom connector
2. Enter https://jaot.io/mcp
3. Complete any authentication prompts

If you prefer to use the config file with the mcp-remote bridge (requires Node.js):

{
  "mcpServers": {
    "jaot": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://jaot.io/mcp",
        "--header",
        "Authorization: Bearer ok_live_your_key_here"
      ]
    }
  }
}

After saving, restart Claude Desktop.

opencode

Add JAOT to your opencode.json (or opencode.jsonc) config file:

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "jaot": {
      "type": "remote",
      "url": "https://jaot.io/mcp",
      "enabled": true,
      "headers": {
        "Authorization": "Bearer ok_live_your_key_here"
      }
    }
  }
}

OpenAI (Responses API)

Pass JAOT as an MCP tool in the tools array of a Responses API request:

{
  "model": "gpt-4o",
  "tools": [
    {
      "type": "mcp",
      "server_label": "jaot",
      "server_url": "https://jaot.io/mcp",
      "headers": {
        "Authorization": "Bearer ok_live_your_key_here"
      },
      "require_approval": "never"
    }
  ],
  "input": "List the available optimization templates."
}

Omit headers (or the Authorization entry) to use only the public catalog and marketplace browse tools.

Cursor

Create or edit .cursor/mcp.json in your project (or ~/.cursor/mcp.json for global):

{
  "mcpServers": {
    "jaot": {
      "url": "https://jaot.io/mcp",
      "headers": {
        "Authorization": "Bearer ok_live_your_key_here"
      }
    }
  }
}

VS Code (GitHub Copilot)

Create or edit .vscode/mcp.json in your workspace. VS Code uses a "servers" root key (not "mcpServers") and requires "type": "http" for remote servers:

{
  "servers": {
    "jaot": {
      "type": "http",
      "url": "https://jaot.io/mcp",
      "headers": {
        "Authorization": "Bearer ok_live_your_key_here"
      }
    }
  }
}

Available Tools

JAOT exposes 19 MCP tools organized into six categories:

Solve Tools

Catalog Tools

File I/O Tools

Marketplace Tools

Execution Tools

Credits Tools

Example Workflows

Solving a Problem from Scratch

An AI agent using JAOT's MCP tools might follow this flow:

1. User: "I need to optimize my delivery routes for 5 warehouses and 20 customers."
2. Agent calls solve_problem with a vehicle routing formulation:

{
  "name": "delivery_routing",
  "variables": [
    {"name": "route_1_2", "type": "binary"},
    {"name": "route_1_3", "type": "binary"}
  ],
  "objective": {
    "sense": "minimize",
    "expression": "12*route_1_2 + 8*route_1_3 + ..."
  },
  "constraints": [
    {"name": "visit_customer_2", "expression": "route_1_2 + route_3_2 + route_4_2 = 1"}
  ],
  "options": {"time_limit_seconds": 60}
}

3. The solver returns the optimal routes with the minimum total distance.

Using a Template

A simpler path for well-known problem types:

1. Agent calls list_templates to see what is available
2. Agent calls get_template("knapsack") to get the input schema
3. User provides item data
4. Agent calls solve_with_template("knapsack", {"capacity": 50, "items": [...]}) to get the solution

Marketplace Path

For pre-built domain-specific models:

1. Agent calls list_catalog_models to browse the marketplace
2. Agent calls get_catalog_model("cat_abc123") to check model details
3. Agent calls get_catalog_model_schema("cat_abc123") to see required inputs
4. Agent calls activate_catalog_model("cat_abc123") to activate for the organization
5. Agent calls execute_model("orgmdl_xyz789", {"input_data": {...}}) to run it
6. Agent calls get_execution to retrieve results

Authentication for MCP Tools

Tools marked "Auth: Yes" require a valid API key. Pass your key in the MCP connection headers as shown in the configuration section above. If a tool requiring auth is called without credentials, it returns an error message explaining how to authenticate.

Tools marked "Auth: No" are publicly accessible and can be used without any API key. This allows agents to browse templates and the marketplace catalog before the user decides to authenticate.

AI Discovery: llms.txt

JAOT also provides standardized discovery documents for AI agents at well-known URLs:

These documents follow the llms.txt specification and allow AI agents to understand JAOT's capabilities without parsing HTML documentation.

Credit Consumption

MCP tool calls that trigger optimization solves consume credits from your organization's balance, following the same pricing formula as direct API calls. Use get_credit_balance to check your balance, and the validate_problem tool to estimate credit cost before solving.

See Rate Limits and Credits for the complete credit pricing formula and plan details.