How to Use the AdaptiveWork (Clarizen) MCP in Cursor

Inject live AdaptiveWork (Clarizen) project requirements straight into your Cursor coding sessions.

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Connect AdaptiveWork (Clarizen) MCP to Cursor

Create your Vinkius account to connect AdaptiveWork (Clarizen) to Cursor 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 AdaptiveWork (Clarizen) with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Live Project Context

Stop switching between your IDE and your project management tabs to check acceptance criteria. Cursor Agent can read your active sprint details and pull the exact requirements into your editor. You stay focused on writing code while the AI fetches the business logic. Ask the agent to run `get_project_details` to grab the metadata for the feature you are currently building. If you need to see the broader initiative, `list_projects` pulls the active states natively so you understand how your code fits into the bigger picture.

Automated Task Updates

Developers hate updating tracking tickets. You can let the AI handle that administrative overhead directly from your terminal. When you finish a module, just tell the agent to log the work. The `create_task` tool adds a new item to the project structure using the exact parent ID you specify. Before creating it, the agent might run `list_tasks` to ensure it doesn't duplicate an existing ticket.

Advanced Clarizen Queries via MCP Server

Complex enterprise environments often hide critical technical requirements deep inside custom fields. Standard API calls might miss the exact architectural notes your PM left for you. You need an MCP connection to dig into the raw database. The `run_query` tool accepts raw CZQL commands to extract highly specific datasets. You can also map these results against the active engineering team by executing `list_users` to see who is assigned to what feature.

Setup guide

Set up AdaptiveWork (Clarizen) MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the AdaptiveWork (Clarizen) MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent AdaptiveWork (Clarizen) transactions." If the MCP tools are loaded correctly, Cursor will call the AdaptiveWork (Clarizen) tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "adaptivework-clarizen-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AdaptiveWork. 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 AdaptiveWork (Clarizen) MCP in Cursor

Create an mcp.json file in your project root or global Cursor directory. Add the Vinkius server URL under the mcpServers object. Switch to Agent mode in the chat panel to start calling tools.

The agent can pull the active task list using the project container ID. It cannot filter by your specific user ID natively, but it can cross-reference the output of `list_tasks` with `list_users` to find your work.

The server itself only fetches project data and manages tasks. Cursor uses that retrieved context to write better, more accurate code based on your actual business requirements.

Ask the agent to map the project structure first. It will use the `list_tasks` tool to read the hierarchy and grab the exact ID needed for the creation payload.

The connection routes through a zero-trust architecture requiring only a single endpoint token. The server processes your task descriptions, project progress metrics, and organizational user lists in memory. Nothing persists on disk after the request finishes.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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