How to Use the Height (Project Management) MCP in Mastra AI

Q: How do I register Height (Project Management) tools in a Mastra AI agent?

Instantiate the client using new MCPClient and pass the server URL. This registers the MCP Server tools so you can call mcpClient.listTools() and spread them directly into your agent configuration.

Q: Can a Mastra AI workflow automatically update tasks in Height (Project Management)?

No, this server only exposes read tools like gettask and listtasks. Your workflows can audit, analyze, and report on project status, but they cannot write changes back to your workspace.

Q: Can I require manual approval before a Mastra AI agent reads my lists?

Yes, you can configure Mastra's requireToolApproval setting for sensitive tools like listlists or workspace. This ensures your agent never accesses project structures through the MCP gateway without a human confirming the action first.

Run automated project audits and track Height (Project Management) activities using Mastra AI workflows with built-in retries.

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Connect Height (Project Management) MCP to Mastra AI

Create your Vinkius account to connect Height (Project Management) 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 Height (Project Management) with Mastra AI

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Build resilient task monitoring loops

Your Mastra AI agent pulls raw project tasks using `list_tasks` within structured workflows that handle API rate limits gracefully. When your automated agents need to monitor project health, network drops shouldn't break your pipeline because this MCP Server retries automatically if the Height API rate limits you. You can set up conditional branches that trigger when a task's status changes. If `get_task` reveals a blocked ticket, the workflow can automatically route the details to the right team lead based on the active assignee data.

Automate workspace activity audits

Your agent registers `list_activities` to check for recent updates across your entire project workspace without manual cron jobs. Use Mastra's workflow engine to parse team output and filter out the noise without writing custom syncing code. The agent reads the raw activity stream, filters out the noise, and uses `workspace` metadata to map updates to specific boards. It is a clean way to generate daily status reports without bugging developers for manual updates.

Map team workloads with Mastra AI

Your workflow queries `list_users` to get your team directory, then cross-references active boards to see where resources are concentrated. Build workflows that automatically audit who is working on what without manual spreadsheet tracking. Since this MCP setup is read-only, your agents can audit and analyze allocation safely using `list_lists`. There is zero risk of an autonomous agent accidentally deleting a project board or misrouting a critical ticket during a run.

Setup guide

Set up Height (Project Management) 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 Height (Project Management) 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: "height-project-management-mcp-client",
  servers: {
    "height-project-management-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Height. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Height (Project Management) MCP in Mastra AI

Instantiate the client using `new MCPClient` and pass the server URL. This registers the MCP Server tools so you can call `mcpClient.listTools()` and spread them directly into your agent configuration.

No, this server only exposes read tools like `get_task` and `list_tasks`. Your workflows can audit, analyze, and report on project status, but they cannot write changes back to your workspace.

Mastra's built-in workflow engine uses automatic retries with exponential backoff. If a heavy `list_activities` call hits API limits, the engine pauses and retries the tool call without failing the entire run.

Yes, you can configure Mastra's `requireToolApproval` setting for sensitive tools like `list_lists` or `workspace`. This ensures your agent never accesses project structures through the MCP gateway without a human confirming the action first.

All task details, user directories, and activity streams pass directly through our secure MCP sandboxes. No project data is stored, and the connection token is encrypted using zero-trust protocols to keep your workspace private.

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