How to Use the Knack MCP in Mastra AI

Q: Can Mastra AI handle complex conditional logic based on Knack schemas?

Absolutely. Mastra AI can use getobjectschema to inspect your Knack table structure and then branch its workflow dynamically depending on which fields are marked as required.

Build resilient, self-healing Knack database workflows with Mastra AI agents that handle retries and approvals.

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Connect Knack MCP to Mastra AI

Create your Vinkius account to connect Knack to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Knack with Mastra AI

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Resilient multi-step updates using Mastra AI

The `update_record` tool integrates into Mastra AI workflows to guarantee database updates succeed even during network drops. If a partial update fails, Mastra's built-in retry engine backs off and attempts the write again automatically via this MCP Server. Before executing any modification, the agent calls `get_object_schema` to verify the payload structure. This ensures your automated workflows never write corrupt data to your Knack tables.

Automated Knack cleanup with human-in-the-loop

The `delete_record` tool allows your Mastra AI agents to purge outdated entries based on custom business logic. Because deleting is destructive, you can configure Mastra's requireToolApproval to pause the workflow until a human approves the deletion. To identify which records need removal, the agent runs `search_records` with specific date filters. It compiles the list, presents it to an admin, and executes the delete operations only after receiving a green light.

Dynamic schema mapping for Mastra workflows

The `list_object_fields` tool provides Mastra AI workflows with the raw schema layout of any Knack table dynamically. This allows your agents to adapt to database changes without you having to redeploy your workflow code. The agent starts by calling `list_objects` to find the correct table key, then pulls the field definitions via the MCP. If a developer adds a new field in Knack, the Mastra agent immediately recognizes it and includes it in subsequent workflows.

Setup guide

Set up Knack MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Knack tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "knack-mcp-client",
  servers: {
    "knack-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Knack Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Knack tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Knack transactions"
);
console.log(result.text);

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Common questions about Knack MCP in Mastra AI

You should enable human-in-the-loop approvals in Mastra AI for the `delete_record` tool. This forces the agent to pause and ask for confirmation before any destructive action is executed on your Knack database.

Absolutely. Mastra AI can use `get_object_schema` to inspect your Knack table structure and then branch its workflow dynamically depending on which fields are marked as required.

You can build a Mastra workflow that loops through your data source and calls `create_record` for each entry. The MCP framework handles rate limits automatically, preventing your Knack API key from getting throttled.

Yes, the agent formats your search queries into the required JSON filter string before calling `search_records`. You don't have to write the escape characters or nested arrays manually.

Your Knack credentials and database records are processed entirely within a zero-trust, ephemeral V8 sandbox managed by Vinkius. Mastra AI accesses this MCP Server using a single secure endpoint token, ensuring your raw database credentials never touch external networks.

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