AdaptiveWork MCP. Manage projects, tasks, and resources via conversation.
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AdaptiveWork (Clarizen) MCP Server connects your AI agent directly to your enterprise project and portfolio data. Your agent handles complex project workflows, from auditing project health and listing active projects to creating granular tasks.
Use it to manage resources, track progress, and run custom data queries without leaving your chat interface.
What your AI agents can do
Create task
Adds a new, granular task to a specified project or parent task structure.
Get project details
Retrieves detailed metadata and current progress metrics for a specific AdaptiveWork project ID.
List projects
Gets a list of all active projects currently managed within the organization.
Retrieves a list of active projects and gives detailed metadata, including progress metrics, for any specific project ID.
Lists all organization users and checks which projects or tasks they are assigned to, helping you see team capacity.
Adds a specific, granular task to a project or a parent task structure, ensuring team accountability.
Pulls a list of all tasks currently associated with a specific project container.
Executes custom queries using Clarizen Query Language (CZQL) to pull highly specific data subsets for reporting.
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AdaptiveWork (Clarizen) MCP Server: 6 Tools for Project Management
Use these tools to interact with your AdaptiveWork account. Run queries, list projects, create tasks, and audit resource assignments using your agent.
019d7546create task
Adds a new, granular task to a specified project or parent task structure.
019d7546get project details
Retrieves detailed metadata and current progress metrics for a specific AdaptiveWork project ID.
019d7546list projects
Gets a list of all active projects currently managed within the organization.
019d7546list tasks
Retrieves all active tasks associated with a given project ID.
019d7546list users
Lists all active organization users to check who is assigned to which project or task.
019d7546run query
Executes advanced Clarizen Query Language (CZQL) commands to retrieve custom, specific data sets.
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What you can do with this MCP connector
AdaptiveWork (Clarizen) MCP Server lets your AI agent handle your whole project and portfolio workflow. You'll get your agent to audit project health, list active projects, and create granular tasks, all without leaving your chat. You can use it to manage resources, track progress, and run custom data queries.
How AdaptiveWork MCP Works
- 1 First, you subscribe to the server and provide your AdaptiveWork API Key and Server URL.
- 2 Your AI client authenticates the connection, establishing a secure link to your enterprise data.
- 3 You prompt your agent with a request—for example, 'List all projects with overdue milestones.' The agent then executes the required tool calls and returns the structured data.
The bottom line is, your agent treats your entire project portfolio like a single database, letting you manage it via conversation.
Who Is AdaptiveWork MCP For?
This is for Project Managers and PMO Leaders who spend too much time clicking between dashboards to get a full picture. It targets the pain of 'dashboard fatigue'—the frustration of having to manually check status reports, resource availability, and task assignments across multiple views. It lets you get that holistic, executive-level view without ever leaving the chat window.
Uses the server to automate task creation and generate status reports for large-scale initiatives, keeping stakeholders updated without manual effort.
Audits portfolio health and tracks resource utilization across multiple departments using the agent to query multiple projects at once.
Retrieves project data and specific task metrics using the run_query tool for financial reporting or performance analysis.
What Changes When You Connect
- Track project health instantly: Instead of opening the dashboard and digging through reports, you ask your agent to 'List all projects with 'Critical' health status.' The agent uses
list_projectsto give you a clean, actionable summary right away. - Stop manual task updates: Need to add a follow-up item? Use
create_taskto build a granular task and assign it immediately. You don't have to navigate to the project, open the task list, and click 'Add'. - Optimize team capacity: Don't guess who's overloaded. Run
list_usersto see every team member and their current assignments. This helps you allocate resources without guesswork. - Get highly specific data: The
run_querytool lets you bypass standard reports. You write a CZQL query and get exactly the data set you need—perfect for financial audits or custom reporting. - Understand the whole portfolio: Use
list_projectsto see every active project, then useget_project_detailson a specific ID. This gives you the full metadata and progress metrics for any project in seconds. - Avoid dashboard overload: The agent handles the complex logic of combining
list_tasksandget_project_details, delivering a single, synthesized answer instead of 15 different tabs and reports.
Real-World Use Cases
The PMO needs a full resource audit.
The PMO Leader needs to know if the development team is over-allocated. They tell their agent, 'Check resource capacity for Q3.' The agent runs list_users and then checks assignments, providing a list of users with insufficient capacity or those who are maxed out, solving the manual audit problem.
A Project Manager needs to track milestones.
Project Alpha is falling behind. The PM asks the agent to 'List all active projects with overdue milestones.' The agent runs list_projects and filters by health status, immediately pointing the PM to the exact projects and tasks needing attention.
The Business Analyst needs financial data.
The BA needs to report on project spending across departments, which isn't in a standard report. They use the run_query tool with specific CZQL syntax, pulling a data set that normal reports simply can't provide.
A Team Lead needs to update tasks quickly.
The team lead needs to assign a review task to a specific person. They tell the agent, 'Add a task named 'Review Budget' to Project Beta, assigned to Jane.' The agent uses create_task and updates the system instantly.
The Tradeoffs
Treating the server like a simple list tool
The user just types 'Show me all projects.' and expects a pretty, filtered table. They ignore the potential for complex queries.
→
Always refine your request. If you need specific data (e.g., status, owner, budget), don't just list. Use list_projects first, then follow up with get_project_details or, better yet, write a targeted query with run_query.
Trying to update tasks manually
The user has to open the project, navigate to the task list, find the task ID, and manually change its status or assign a new owner.
→
Use create_task to add a new task, or ask the agent to manage the lifecycle. If you need a status change, ask the agent to execute the necessary process flow, rather than trying to replicate the UI clicks.
Ignoring resource constraints
The PM starts assigning tasks without checking if the assignee has bandwidth, leading to bottlenecks and missed deadlines.
→
Before assigning, run list_users to see the team roster, and then prompt the agent to check assignments against the project ID. This prevents over-allocation and ensures realistic planning.
When It Fits, When It Doesn't
Use this server if your job requires connecting project status, task management, and resource tracking. You need an AI agent to synthesize data across multiple views and perform atomic updates. It's perfect for PMOs and PMs who need to audit portfolio health quickly.
Don't use this if your core need is simple data storage or basic form submission. If you just need to read a few values or run a single, isolated report, a dedicated data retrieval tool might be cleaner. If your process involves complex, asynchronous, multi-system logic (like triggering external emails or running financial calculations outside of Clarizen), you need a different integration layer.
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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 6 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Checking project status shouldn't require opening five different tabs.
Today, checking the health of a project means opening the main dashboard, clicking into the task view, switching to the resource allocation tab, and then pulling a separate report for the budget. You copy-paste status updates into a spreadsheet, and it takes 30 minutes of clicking and switching tabs just to get an executive summary.
With the AdaptiveWork (Clarizen) MCP Server, you ask your agent: 'What is the health status of Project Gamma?' The agent runs `list_projects` and synthesizes the entire status—including overdue tasks, resource gaps, and current phase—and presents it in a single, conversational reply.
AdaptiveWork (Clarizen) MCP Server: Task Orchestration
The manual steps that go away are navigating to the project, finding the task list, and then using the 'Add Task' button. You don't need to open the task view, find the correct parent ID, and then manually input the task name and description.
Now, you simply tell your agent: 'Create a task called 'Review Budget' for Project Alpha.' The task is created, assigned, and logged instantly. It's a direct action, eliminating the clunky UI workflow.
Common Questions About AdaptiveWork MCP
How do I use the `run_query` tool in the AdaptiveWork (Clarizen) MCP Server? +
You must provide valid CZQL syntax in your prompt. The agent executes the query and returns the specific data set. This tool is for custom reporting that standard project reports can't handle.
Can I list all active projects using the `list_projects` tool? +
Yes, list_projects retrieves a list of all active projects managed in your AdaptiveWork organization. You can also filter this list by status or state directly in your prompt.
How does `create_task` work in the AdaptiveWork (Clarizen) MCP Server? +
To create a task, you must provide both the task name and the ID of the parent project or task. The agent handles the API call to add the new granular task.
Is `list_users` the right tool for checking resource assignments? +
Yes. list_users retrieves the full list of active organization users, allowing your agent to check their assignments and capacity for resource planning.
Can the AdaptiveWork (Clarizen) MCP Server get detailed metrics for one project? +
You use get_project_details and provide the specific Project ID. This tool pulls detailed metadata and progress metrics for that single AdaptiveWork project.
How do I retrieve a list of tasks for a specific project using the `list_tasks` tool? +
You use list_tasks and must provide the Project ID. This tool pulls all active tasks associated with that project container, allowing you to see the entire scope of work for that initiative.
What project information can I get using `get_project_details`? +
The get_project_details tool returns detailed metadata and progress metrics for a single project. You can check its current health status, key milestones, and overall progress against its defined goals.
What happens if I run a query with invalid CZQL syntax using `run_query`? +
The system will return a specific error message detailing the CZQL syntax failure. You'll need to check the Clarizen documentation for correct syntax before trying the query again.
How do I find my AdaptiveWork API Key? +
Log in to AdaptiveWork, go to Settings > Extensions. You can generate or retrieve your API key from the API section. Make sure your user profile has 'API User' permissions enabled.
What is CZQL? +
CZQL (Clarizen Query Language) is a SQL-like language used to query the AdaptiveWork database. It allows for complex filtering, sorting, and data retrieval across all your entities.
Can I manage multiple project locations? +
Yes! Use the list_projects tool to view all projects across your entire organizational structure, regardless of their location or department.
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Connect this server to Cursor, Claude, VS Code, and more.
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