MCP Servers and AI Tools

What are MCP servers?

MCP (Model Context Protocol) servers give your Velaro AI bots access to real-time tools — database lookups, API calls, order status checks, and more. Instead of hard-coding every integration into a workflow, you connect an MCP server once and the AI bot can call its tools naturally in conversation.

Example: a visitor asks "What is the status of order #8821?" The bot calls the get_order tool on your MCP server, retrieves the live order data, and replies — all without an agent.

Connecting an MCP server

1. Go to MCP Servers in the sidebar (under Integrations).

2. Click Add MCP Server.

3. Enter:

- Name — a label for your team (e.g. "Order Lookup API")

- URL — the HTTPS endpoint of your MCP server

- API Key — if your server requires authentication

4. Click Test Connection — Velaro will discover the available tools.

5. Click Save.

The tools on this server are now available to any AI bot in your account.

Using MCP tools in a bot

1. Open the AI Bots section.

2. Edit the bot that should use the tools.

3. Under Tools, toggle on the MCP server(s) you want this bot to use.

4. In the system prompt, describe when and how the bot should call the tools. Example:

When a customer asks about an order, use the get_order tool with their order number.
Always confirm the order number before calling the tool.

5. Save and activate the bot.

Building your own MCP server

An MCP server is any HTTPS endpoint that responds to the MCP protocol. Velaro-compatible servers expose a tool manifest at GET /tools and accept tool calls at POST /tools/{toolName}.

Minimal Node.js example:

const express = require('express');
const app = express();
app.use(express.json());

app.get('/tools', (req, res) => {
  res.json({ tools: [
    {
      name: 'get_order',
      description: 'Look up an order by order number',
      parameters: {
        type: 'object',
        properties: {
          orderNumber: { type: 'string', description: 'The order number' }
        },
        required: ['orderNumber']
      }
    }
  ]});
});

app.post('/tools/get_order', async (req, res) => {
  const { orderNumber } = req.body;
  // fetch from your database
  const order = await db.orders.findOne({ id: orderNumber });
  res.json({ result: order });
});

app.listen(3000);

Host this on any cloud provider (Vercel, Railway, AWS Lambda, Azure Functions) and add the URL in Velaro.

Security best practices

• Always use HTTPS — Velaro will not connect to plain HTTP endpoints.
• Use an API key to restrict access to your server to Velaro only.
• Return only the data the bot needs — do not expose entire database records.
• Set rate limits on your MCP server to prevent runaway tool calls.

Tool call limits

Your plan includes a limit on MCP tool calls per conversation and per month. These limits prevent runaway loops and control costs. You can see current usage in Billing > Usage. Contact your account manager to increase limits.

AI Orchestration (multi-bot delegation)

With orchestration enabled, one AI bot can delegate to another. For example, your main customer service bot can hand off to a specialized "technical support bot" for complex questions, then resume when it's done.

To set up delegation, your primary bot's system prompt should include:

If the customer has a billing question, delegate to the billing_specialist bot.
If the customer has a technical question, delegate to the technical_support bot.

Velaro handles the handoff automatically. The conversation history is preserved across both bots.

Troubleshooting MCP connections

"Connection failed" — check that the server URL is correct, uses HTTPS, and is publicly accessible. Verify the API key.

"No tools found" — ensure your server's GET /tools endpoint returns a valid tool manifest.

"Tool call timed out" — your MCP server must respond within 15 seconds. Optimize slow database queries or add caching.

Tools not being called — add explicit instructions to the bot's system prompt telling it when and how to use each tool.