Compatible with every major AI agent and IDE
Create message on Teamwork Projects
Body should include title and body content. Post a new message in a project
Create milestone on Teamwork Projects
Body should include title and deadline date. Create a new milestone in a project
Create project on Teamwork Projects
Body should include name and optional settings. Create a new project
Create task on Teamwork Projects
Body should include content, tasklist_id, assignee_ids, and due dates. Create a new task
Create time entry on Teamwork Projects
Body should include description, duration, and date. Log a new time entry
Delete task on Teamwork Projects
Delete a task
Get current user on Teamwork Projects
Use this to verify connection and identify your user ID. Get the authenticated user profile
Get project on Teamwork Projects
Get details of a specific project
Get task on Teamwork Projects
Get details of a specific task
List files on Teamwork Projects
List all files in a project
List messages on Teamwork Projects
List all messages in a project
List milestones on Teamwork Projects
List all milestones in a project
List projects on Teamwork Projects
Use project IDs to query tasks, milestones, and other resources within specific projects. List all projects accessible to the user
List tasklists on Teamwork Projects
Use task list IDs to query specific tasks. List all task lists in a project
List tasks on Teamwork Projects
List all tasks in a project
List time entries on Teamwork Projects
List all time entries in a project
Update task on Teamwork Projects
Update an existing task
How Vinkius protects your data
Can I log time against a project?
Yes! Use the create_time_entry action with a JSON body that includes description, duration (in minutes or seconds), and date.
Can I audit what my AI agents are doing with this integration?
Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Triggering Teamwork Projects via Natural Language
Securely interface Claude Code, ChatGPT, and Cursor with the Teamwork Projects API through semantic routing and standardized natural language triggers.
Scaling task management via MCP
Add task management functionality to your custom chatbots. The Teamwork Projects MCP handles the payload formatting required for ChatGPT and Claude to interface with productivity endpoints.
Optimizing milestone tracking with Claude
Use Teamwork Projects to interface with milestone tracking via natural language. The toolkit provides Cursor with LLM-friendly schemas for productivity tasks.
Teamwork Projects. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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