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

Q: Can Mastra AI automatically retry failed Hive (Project Management) tool calls?

That is the main benefit of the framework. If a call to createaction times out, the engine applies exponential backoff and tries again.

Q: How do I handle multiple workspaces?

Have your workflow call listprojects first to build a map of available locations. The agent uses this map to route subsequent API calls to the correct destination.

Build reliable Hive workflows that handle API failures automatically using Mastra AI. Let your agents manage tasks without babysitting.

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Connect Hive (Project Management) MCP to Mastra AI

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

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Automate task triage

The `list_actions` tool lets your Mastra AI agent pull a backlog of untriaged work. It reads the descriptions, decides where they belong, and updates them automatically. If the initial query fails due to network issues, the framework applies exponential backoff. You get a resilient pipeline that sorts tickets without human intervention.

Conditional branching with MCP Server

The `get_action` tool exposes core status data so your workflows can react to changing conditions. A workflow might check a status, and if the task is blocked, branch off to notify a manager. If the status is clear, it proceeds to `create_action` to spawn the next phase of the project. You define the logic, and the agent executes the correct tool based on the live data.

Standardize cross-team projects

The `list_templates` tool forces your agents to use approved formats when generating new work. It stops rogue scripts from cluttering your boards with unformatted text. Combine this with `list_workspaces` to ensure tasks land in the correct department. Your workflow engine maps the template to the workspace before creating the final record.

Setup guide

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

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

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

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

Initialize a new client instance and pass your server URL in the configuration block. Then call the tool listing method and spread the results into your agent's tool array.

That is the main benefit of the framework. If a call to `create_action` times out, the engine applies exponential backoff and tries again.

You control this via the approval flag. Turn it on for destructive actions or leave it off if you trust the agent to manage its own queue.

Have your workflow call `list_projects` first to build a map of available locations. The agent uses this map to route subsequent API calls to the correct destination.

The connection touches your internal project labels and action comments. Authentication requires a single endpoint token, and the zero-trust architecture ensures no residual data remains after the workflow completes.

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