Plecto MCP. Turn BI data requests into conversational commands.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Plecto connects your AI agent directly to your business intelligence platform, letting you manage KPIs, track performance, and orchestrate dashboards using natural conversation.
You can use `list_kpi_dashboards` to see all active boards or use `create_data_registration` to feed new data points immediately. It’s built for BI teams who need real-time access to team structures and performance metrics.
What your AI agents can do
Get dashboard
Retrieves the specific details and metadata for one configured KPI dashboard.
Get employee
Fetches detailed information about a single employee by name or ID.
Get registration
Gets the full details and history for one specific data registration entry.
The server retrieves metadata for existing dashboards (list_kpi_dashboards) or fetches specifics about a single board using get_dashboard.
You can programmatically add new data entries to feed KPIs directly into the system via create_data_registration.
The server lists all teams and employees (list_organizational_teams, list_account_employees) so your agent knows who's in the company.
You can list available data sources using list_data_sources to ensure your queries are scoped correctly before running any reports.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Plecto MCP Server: 11 Tools for BI Ops
These tools allow your AI agent to interact with every part of the Plecto platform—from logging a single data point to listing all team members.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Plecto on Vinkius019dd13dget dashboard
Retrieves the specific details and metadata for one configured KPI dashboard.
019dd13dget employee
Fetches detailed information about a single employee by name or ID.
019dd13dget registration
Gets the full details and history for one specific data registration entry.
019dd13dlist formulas
Lists all the custom KPI calculation formulas used across your dashboards.
019dd13dlist widgets
Retrieves a list of every individual widget component on a specified dashboard.
019dd13dcreate data registration
Adds a new data point to update an existing metric on your dashboard.
019dd13dlist kpi dashboards
Retrieves a list of every active and configured KPI dashboard available for monitoring.
019dd13dlist data sources
Queries and lists every configured data source available in your Plecto setup.
019dd13dlist account employees
Retrieves a list of all employees managed under your Plecto account.
019dd13dlist data registrations
Lists all historical data records and registrations stored in Plecto.
019dd13dlist organizational teams
Lists all formal organizational teams within your account structure.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Plecto, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Plecto. 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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
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 11 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Tracking performance means clicking through too many screens.
Right now, if you need to check one KPI, you might have to jump between the main dashboard, then click into a specific widget's detail view, and finally pull up the source data sheet just to confirm the number. It’s three separate systems, five clicks deep.
With this MCP server, you tell your agent exactly what metric you need—say, "What was the Q1 sales average?" Your agent runs `list_kpi_dashboards` and drills down into the right board, giving you the final number in a single chat response. No clicks needed.
Plecto MCP Server: Manage dashboards and data flow.
Manual processes require exporting CSVs from the dashboard, updating them locally, and then re-uploading everything back into Plecto. This process is slow, prone to format errors, and always takes half a day.
This server eliminates that cycle. You simply use `create_data_registration`. Your agent handles the data formatting and API submission, making the entire reporting loop instant.
What you can do with this MCP connector
You're done manually building reports and wrestling with dashboards. Plecto hooks your AI agent right into your business intelligence platform so you can manage KPIs, track performance data, and orchestrate complex metrics just by chatting with it. Your agent uses these tools to do the heavy lifting, letting you focus on what actually matters: making decisions.
Dashboard Oversight and KPI Querying
Your agent handles dashboard queries two ways. If you want a bird's-eye view of everything set up, it runs list_kpi_dashboards to pull every active and configured KPI board name. Need the deep dive on one specific metric? It uses get_dashboard to retrieve all the granular details and metadata for that single dashboard you mention.
When your agent pulls data from a widget, it's not guessing; it knows exactly which board it belongs to.
Logging Live Performance Data
For real-time number crunching, your agent can feed live numbers directly into your KPIs using create_data_registration. This function lets you programmatically add a brand new data point to update an existing metric on any dashboard. If you're checking historical performance or need the full audit trail on a specific value, it runs list_data_registrations to give you a list of every stored data record and registration in Plecto.
To see exactly what happened with one entry—the metadata, the history, everything—it hits get_registration. This whole system means your dashboards never show stale numbers.
Understanding Your People and Teams
When it comes to resource management, your agent knows who's in the building. It uses list_organizational_teams to pull a complete list of all formal organizational teams within your account structure. If you need to know every single person under your Plecto umbrella, it runs list_account_employees to get that master roster.
And if you're asking about one specific individual—say, 'Jane Doe' or an employee ID—it uses get_employee to fetch all their detailed information right away.
Data Source and Formula Inspection
Your agent doesn't just pull numbers; it understands where the numbers come from. Before running any report, it can use list_data_sources to query and list every single configured data source available in your Plecto setup. This ensures that any reports generated are scoped correctly against the right feed. Furthermore, if a KPI is based on a complex calculation, you don't have to guess what formula was used.
It runs list_formulas to pull a complete list of every custom KPI calculation formula deployed across your dashboards. Knowing these formulas lets your agent validate results and explain exactly how the number was calculated.
How It Works With Your Agent
Your setup is simple: You subscribe to this server on Vinkius, and then you feed your Plecto API Token into your preferred AI client or agent. You don't write code; you just talk to it. You can ask things like, "What was the average sales metric for Q3?" or "Show me all the teams that report to Marketing." Your agent uses this toolkit—the list_kpi_dashboards, the get_employee, and the create_data_registration functions—to get the raw data, process it against your formulas, and present you with a clean answer.
It's all conversational, always real-time, and built for BI teams who need immediate access to performance metrics and internal structure.
019dd13d-a7ff-7219-8226-fe0d3a6c1aae 
How Plecto MCP Works
- 1 First, subscribe to the Plecto MCP Server and get your API Token from your Plecto account.
- 2 Next, paste that token into your preferred AI client (Claude, Cursor, etc.)'s settings.
- 3 Finally, tell your agent what you need—like 'Show me all KPI dashboards for Q2,' and it runs the necessary tools.
The bottom line is: You connect your existing BI platform to conversational AI so you can treat complex data tasks like sending a Slack message.
Who Is Plecto MCP For?
This is for the Operations Manager who's tired of manually pulling reports from five different dashboards. It’s for the BI Analyst needing instant access to metadata, and any Project Lead whose job requires knowing exactly which team owns which data source. If your workflow involves reading metrics or managing people resources, you need this.
Uses list_kpi_dashboards and get_dashboard to quickly audit available performance boards without navigating the UI.
Relies on list_account_employees and list_organizational_teams to verify team access and resource allocation for new projects.
Uses create_data_registration when a project milestone is hit, feeding the closed revenue or completion count directly into the main dashboard.
What Changes When You Connect
- Automated Data Logging: Instead of manually updating spreadsheets, use
create_data_registrationto feed real-time numbers directly into your KPIs. Your agent handles the API call, and the dashboard updates instantly. - Total Dashboard Visibility: Need to know what boards exist? Running
list_kpi_dashboardsgives you an immediate inventory of every KPI board without clicking through multiple menus. - People Lookup on Demand: Stop asking HR or your teammates for employee directories. Use
list_account_employeesandget_employeeto pull specific contact details or roles instantly when needed. - Contextual Data Scope: Before querying anything, run
list_data_sources. This ensures your agent knows exactly which data set it's pulling from, preventing bad reports based on wrong context. - Team Structure Mapping: Quickly check who belongs where. Running
list_organizational_teamsgives you the full team breakdown, letting you manage access and resource allocation in one prompt.
Real-World Use Cases
End-of-Month Reporting
The Project Lead just closed a big deal. Instead of logging into Plecto's interface to manually update the 'Revenue' metric, they tell their agent: 'Run create_data_registration for Sarah Chen with $127k in revenue.' The system logs it, updates the dashboard widget, and sends a notification automatically.
Auditing Dashboard Health
The BI Analyst needs to know if a specific KPI board is still active or if widgets are broken. They ask their agent to use list_kpi_dashboards, then select the troubled dashboard and run list_widgets to see exactly what components need fixing.
Onboarding New Team Members
The Operations Manager needs to confirm if a new hire, Jane Doe, is assigned to the correct department. They ask their agent to use get_employee for Jane's details and then check list_organizational_teams to verify her placement against current resource limits.
Verifying Data Scope
The Data Scientist is building a new report but isn't sure if the 'Client Address' data source is available. They run list_data_sources first, confirm its status, and then use get_registration to check the last time valid data was pulled.
The Tradeoffs
Asking for a number without context
Prompting the agent with: 'What is the total team revenue?' The agent fails because it doesn't know which dashboard or data source to query.
→
Don't just ask for the metric. First, use list_kpi_dashboards to narrow down the board name. Then, tell your agent: 'Get the KPI dashboard named 'Q2 Sales Overview', and give me the current total team revenue figure.'
Assuming a data point exists
Trying to report a sale for an employee who might have changed names or roles. The agent returns ambiguous errors.
→
Always cross-reference user details first. Use list_account_employees to get the current, official list of employees before attempting any actions like create_data_registration.
Running reports on old data
Getting a report that looks correct but uses numbers from two weeks ago. The dashboard is out-of-sync.
→
Check the source first. Run list_data_sources to check the last sync time, and then use get_registration to verify the specific data entry's timestamp before trusting any number.
When It Fits, When It Doesn't
Use this server if your workflow is centered on querying performance metrics (KPIs), managing organizational resources, or logging structured business events. If you need to know what dashboards exist (list_kpi_dashboards), list employees (get_employee), or log a closed deal (create_data_registration), this is the right tool.
Don't use this if your primary task is data cleaning (use dedicated ETL tools) or if you just need to write simple text reports. If all you need is basic team communication, an email client works fine. But when the goal is turning conversational prompts into structured, auditable changes in a BI tool—this server is essential.
Common Questions About Plecto MCP
How do I find out what KPI dashboards are available using list_kpi_dashboards? +
You tell your agent to run list_kpi_dashboards. It will give you a full, current list of every dashboard configured in Plecto, letting you know exactly which metrics exist.
Can I update the board with create_data_registration? +
Yes. create_data_registration lets your agent log a new data point (like closed revenue) and immediately feed it into the dashboard, updating the widgets in real time.
What is the difference between list_account_employees and get_employee? +
list_account_employees gives you a full directory—a list of every person. get_employee requires you to pinpoint one specific person so your agent can pull their exact details.
Does the server help me track data sources with list_data_sources? +
It does. Running list_data_sources shows every context available in Plecto, making sure you and your agent know exactly which source is feeding which numbers.
If I use `list_formulas`, how do I get the actual calculation logic for a specific KPI? +
The server lists all available KPI formulas. To see the detailed logic, you must then pass the formula ID to the dedicated metadata endpoint (reference the documentation). This reveals exactly which data sources and metrics feed into that calculation.
What does `list_widgets` show me? Can I figure out how a dashboard is built? +
list_widgets gives you an inventory of every component on a given board. It lists the widget type (e.g., chart, gauge) and which data source it pulls from. This helps map the entire dashboard structure.
What’s the practical difference between calling `list_data_registrations` and using `get_registration`? +
Calling list_data_registrations shows you a summary list of all your data entries. You need get_registration when you want to pull the full, granular details—like timestamps or metadata fields—for one specific record.
If I run a complex action like `create_data_registration`, how does the server handle API token expiration or bad data? +
The server validates your connection credentials immediately. If the API token is expired or invalid, the call fails instantly with an authentication error code before any action happens. Bad data formats will trigger a specific validation failure.
Can I add a new data registration using my AI agent? +
Yes! Use the create_data_registration action. Provide the Data Source ID along with your data fields to feed your dashboard programmatically.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.