Zenkit MCP. Manage structured data and lists across all workspaces.
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Zenkit lets your AI agent interact directly with structured data across multiple workspaces and collections. Use this MCP to programmatically read, write, update, or delete entries in your knowledge base, making it a central hub for managing operational records from any client application.
What your AI agents can do
Create entry
Builds a brand new data record in a specific list, requiring you to provide the field values for that item.
Delete entry
Permanently removes an existing record from your specified Zenkit list.
Get list details
Retrieves the full metadata and structure definition for a specific Zenkit collection.
Lists every workspace available to you and shows which lists belong to them.
Retrieves the full configuration, including field types, for a single Zenkit list.
Lists every existing entry (item) within a chosen data list.
Creates an entirely new record, requiring you to supply the specific field values for that item.
Changes one or more fields on a record that already exists in your collection.
Deletes a specific entry from a list, keeping the list structure intact.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Zenkit MCP: 8 Tools Available
These tools let your agent handle every aspect of Zenkit data management, from listing the main workspaces to creating and modifying individual records.
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Start using Zenkit on Vinkius019d7627create entry
Builds a brand new data record in a specific list, requiring you to provide the field values for that item.
019d7627delete entry
Permanently removes an existing record from your specified Zenkit list.
019d7627get list details
Retrieves the full metadata and structure definition for a specific Zenkit collection.
019d7627get workspace details
Fetches detailed information about a single workspace within your account.
019d7627list elements
Shows all the defined fields (columns) that make up a specific list's data structure.
019d7627list entries
Provides a summary view of every item in a list, often with filtering capabilities.
019d7627list workspaces
Lists all the main workspaces you have access to and which lists belong inside them.
019d7627update entry
Modifies one or more fields on a record that already exists in your Zenkit list.
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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 8 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
The pain of switching tabs to keep project data current
Right now, tracking a single item's progress means jumping between the main task list, the asset library, and the owner contact sheet. You copy the ID from one tab, paste it into another, then switch over again just to update the status field. It’s tedious clicking, manual data entry, and a constant risk of error.
With this MCP, you tell your agent what needs updating. If Project Alpha hits a milestone, you simply ask: 'Set Project Alpha's status to Complete.' The agent executes that change directly within Zenkit, eliminating the need for multiple clicks and ensuring the data is updated in one clean step.
Get structured access with the Zenkit MCP
You no longer have to rely on exported CSVs or screenshots. The agent can use `get_list_details` and `list_elements` first, giving you a blueprint of what data exists. Then, it uses that knowledge to execute precise commands like `create_entry`, building out the record exactly how Zenkit expects.
The process moves from 'Copy-Paste-Guess' to 'Command-Execute-Verify.' You get reliable, structured writes every time.
What you can do with this MCP connector
This connection gives your agent the ability to manage complex project information stored in Zenkit. Instead of opening multiple tabs and manually copying data between different sections, you can ask your agent to perform actions like listing all available workspaces or retrieving specific details about a collection’s structure. You can command it to fetch all existing entries within a list, create new records with defined fields, or modify statuses on old items.
If you're building automations that need to manage data across several platforms—say, updating project status in Zenkit after logging a sale in a CRM—you can chain this MCP together with others, running the entire workflow through one AI agent connected via Vinkius. This makes sure your keys pass through our zero-trust proxy and are used only in transit, meaning nothing is ever stored on disk.
019d7627-9ccd-722b-93ec-fb145b129eac 
How Zenkit MCP Works
- 1 Subscribe to this MCP and input your Zenkit API key.
- 2 Connect your preferred AI client (Claude, Cursor, etc.) to Vinkius using that single connection.
- 3 Your agent can then execute commands against the structured data in Zenkit.
The bottom line is: you tell your agent what data change needs to happen, and it executes the action directly inside Zenkit.
Who Is Zenkit MCP For?
Anyone who lives where structured documentation meets operational workflow. This is for the project manager tired of manually syncing status updates across five different dashboards, or the operations engineer whose job requires consistent data cleanup and record maintenance.
Uses this to audit task lists across departments, confirming every team member's current project status without opening multiple web tabs.
Automates data entry and record maintenance. When a new client signs up, the agent can automatically create the initial set of records in Zenkit for onboarding documentation.
Quickly builds internal guides by having the agent retrieve all relevant information from different collections and compiling it into one summary document.
What Changes When You Connect
- Audit project status instantly. Instead of manually checking multiple dashboards, your agent can use
list_workspacesto map out every department's current projects. - Eliminate manual content creation. Need a new record? Use
create_entryand simply describe the data you want, letting the MCP structure it correctly in Zenkit. - Keep your knowledge base clean. If an entry is obsolete, use
delete_entry. Your agent handles the cleanup process via natural language command. - Maintain data integrity with confidence. You don't have to worry about how keys are handled; Vinkius ensures credentials pass through a zero-trust proxy and never sit on disk.
- Deep dive into structure. Use
list_elementsbefore updating anything. This lets you inspect the list’s field types, so your agent knows exactly where to write the data.
Real-World Use Cases
Discovering all project scopes
A PM needs a report showing every active collection across the company. Instead of clicking through five different workspace folders, they prompt their agent: 'List all my Zenkit workspaces and what lists are inside.' The agent uses list_workspaces to return the full map instantly.
Mass updating status records
The marketing team finishes a quarterly review. Instead of manually logging into 3 different list views, they tell their agent: 'Update all entries in the Assets library that are marked 'Draft' to 'Final' and set the owner field to Jane Doe.' The agent uses update_entry for bulk changes.
Building a new structured guide
An HR manager needs a new onboarding list. They prompt: 'Create a new Zenkit collection called 'New Hire Checklist' with fields for Start Date, Manager Email, and Policy Agreement.' The agent handles the setup using get_list_details to confirm structure before creating it.
Auditing historical data
An auditor needs to see all records associated with a specific product line from last year. They ask their agent to 'List all entries in the Product History list filtered by 2023.' The agent uses list_entries to provide an immediate, structured audit trail.
The Tradeoffs
Trying to update without knowing fields
Prompting the agent: 'Update entry 123 with new data.' The system fails because it doesn't know what fields are available or how to format the payload.
→
First, run list_elements on the target list. Then, structure your request using the discovered field names and call update_entry. This ensures the payload matches the schema.
Over-listing data
Asking the agent to 'Show me all entries in this list.' This returns thousands of records, making it useless for immediate action.
→
Use list_entries and include explicit filters or constraints in your prompt. Always narrow the scope before asking for a full dump.
Manually deleting data
A user deletes an item manually, but then forgets to update related fields in another linked list.
→
Use delete_entry through your agent. You can wrap this deletion call within a larger workflow that triggers dependent cleanup actions automatically.
When It Fits, When It Doesn't
Use this MCP if the data you manage lives in structured lists, workspaces, and collections (i.e., it needs columns, defined fields, and statuses). This is perfect for project tracking, CRM records, or knowledge bases built on a database model. Don't use it if your core need is simply drafting an email, composing a chat message, or processing unstructured text files; those require messaging or document-storage tools instead. If you only need to read data and never write or change anything, list_entries and list_elements are enough. But if you need to build automation that modifies records—like updating status using update_entry—then this is exactly what you need.
Common Questions About Zenkit MCP
Can I use the zenkit MCP to find out what lists are in a workspace? +
Yes. Use list_workspaces first to see all available workspaces. Then, you can drill down using get_workspace_details to list the constituent collections within that environment.
How do I update an entry using the zenkit MCP? +
You must use the update_entry tool. Before running it, check the field names by calling list_elements to ensure your payload matches the list's defined schema.
What is the difference between listing entries and getting list details in zenkit? +
The get_list_details tool gives you the blueprint—the structure, fields, and configuration of the collection itself. The list_entries tool actually retrieves the content—a summary view of all items currently inside that structured container.
Does zenkit MCP let me create entries for multiple lists? +
You can't do it in a single call, but you can chain calls. You'd use create_entry separately for each list and wrap those sequential actions into one agent workflow.
How do I use `list_elements` to check what fields are available in a specific list? +
It returns the precise data structure of any given list. This lets your agent know exactly which field types and names you can use when creating or updating entries, preventing schema errors.
What happens if I try to use `create_entry` with incorrect or missing JSON field values? +
The MCP validates the input against the target list's schema first. If any data is invalid or a required field is missing, the call fails and returns an error message detailing exactly what needs correcting.
Is there any safety check when using the `delete_entry` tool? +
Yes, the agent will prompt you for confirmation before executing a deletion. This built-in safeguard ensures you can't accidentally wipe out important records with a single command.
Besides listing data, what metadata can I get using `get_workspace_details`? +
This tool provides high-level information about the entire workspace. You retrieve details like list counts and overall configuration settings—perfect for getting a quick structural overview.
How do I find my List ID? +
Use the list_workspaces tool to see all your workspaces and the lists they contain along with their unique IDs.
Can I filter entries in a list? +
The current list_entries tool retrieves all items. For complex filtering, you can provide field-specific values when using the create or update tools.
Is it possible to see the field definitions of a list? +
Absolutely. Use the list_elements tool with a list ID to retrieve all field names, types, and configurations.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.