Naise MCP Server Documentation

About

The Naise MCP server allows you to access your data housed within Naise using natural language within a variety of AI platforms, such as Claude, Cursor, and Gemini. All tools are read-only, ensuring your payroll and employee data remains secure while providing powerful query capabilities.

Important Security & Usage Guidelines

Please adhere to the following critical guidelines:

Use the Naise MCP Server in Isolation

To prevent potential data leakage and ensure the integrity of your session, use the Naise MCP server in an isolated environment. Do not connect other MCP servers to the same client session that is connected to Naise. Mixing servers can lead to unpredictable behavior, including the potential for your Naise data to be inadvertently sent to another service.

Connect with Trusted Clients Only

Please connect to the Naise MCP server only through trusted, well-established MCP clients such as Claude, Gemini and Cursor. Using unverified or untrusted clients could expose your sensitive data to security vulnerabilities.

Require Manual Confirmation for All Tool Use

LLMs can sometimes misinterpret prompts. To prevent unintended data access, it is critical that you don't enable any automatic tool execution features in your client. You should always be prompted to confirm any tool call before it is executed. This gives you final control and helps ensure the model is only accessing the data you explicitly approve.

Review All Tool Calls Before Approval

Before approving any tool call, carefully review what data the LLM is requesting. The AI may inadvertently request sensitive payroll or employee information that could then be exposed to other services. Be especially cautious of AI features that perform external web searches or use additional tools, as your company's sensitive data retrieved from Naise could potentially be sent to external search engines or third-party services. Always verify that the tool calls are appropriate and necessary for your query before allowing them to execute.

Verify All Outputs for Accuracy

Treat all LLM-generated responses as a starting point, not a final source of truth. Always verify the accuracy of both the tool calls the model suggests and the final responses it generates. Because LLMs can occasionally misinterpret data or "hallucinate" information, it's critical that any data presented to you is correct before acting on it.

Opt-Out of Model Training

Your prompts and the resulting responses may contain sensitive information. To protect this data, you must configure your LLM client to opt out of sharing data for model training purposes. Most major providers offer this privacy setting, which may be labeled as "Chat history & training" or similar. Failure to do so could result in your sensitive company data being stored and used by the third-party LLM provider.

Capabilities

Our MCP server provides an OAuth2 based connection process and allows you to select the categories of data to which your chosen LLM will have access, directly shaping its capabilities.

Available Data Categories

When connecting, you can grant access to:

Company Information: Basic company details, locations, and settings
Employee Data: Employee profiles, job titles, departments, compensation
Contractor Data: Contractor information and payment details
Payroll Data: Payroll runs, pay schedules, tax information, and deductions
Time Tracking: Time-off balances, sick leave, vacation accruals

Read-Only Access

All tools provided by the Naise MCP server are read-only. The server can retrieve and analyze your data but cannot:

Execute payroll runs
Transfer money
Create, modify, or delete employees
Change compensation or benefits
Modify company settings

This ensures your data remains secure while providing powerful query and analysis capabilities.

Getting Started

Prerequisites

Claude: Claude Pro or Max subscription
Cursor: Cursor Pro, Pro+, Ultra, Teams or Enterprise
Gemini: Gemini CLI installed

Setup for Claude

Click your avatar in the bottom left corner of the Claude interface
Click "Settings"
Navigate to "Connectors" in the left nav
Click "Add custom connector"
Input "Naise" as the Name
Input the Remote MCP server URL: https://naise.app/mcp
Click "Add"
If you see "Configure" next to "Naise," click the ellipsis (...), select "Disconnect" and confirm the disconnection
Click "Connect"
Select the desired data types for which you'd like to provide access and, if applicable, the company you'd like to connect
Click "Authorize"
Open up a new chat
Confirm the Naise MCP server is active via the "Search and tools" button, which is found to the right of the "+" button within the chat input
You're now ready to input your first query!

Setup for Cursor

Within the Cursor IDE, go to "Cursor" (in the menu bar) → "Cursor Settings"
Click "Tools & Integrations"
Under "MCP Tools," click "New MCP Server"
Input the following into the automatically generated mcp.json file:

JSON

{

"mcpServers": {

"naise-mcp": {

"url": "https://naise.app/mcp/"

}

Save the updated file
Click "Needs login" under "naise-mcp"
Click "Open"
Log in to your Naise account
If there are multiple companies, select the relevant company
Click "Authorize"
Click "Open Cursor"
Within the "AI Pane," open up a New Chat
Begin using the server with prompts like: "Limit this chat to MCP: 'naise-mcp'"

Setup for Gemini CLI

Prerequisites: Gemini CLI must be installed (installation instructions)

Add the following to your Gemini settings.json file (located in the .gemini folder):

JSON

{

"mcpServers": {

"naise": {

"httpUrl": "https://naise.app/mcp"

}

Start the tool using gemini
Authenticate using one of the methods provided
Input /mcp auth naise
Log in to your Naise account
If there are multiple companies, select the relevant company
Click "Authorize"
Confirm the MCP server is connected by inputting /mcp list
Begin testing!

Example Use Cases

Here are practical examples of how to use the Naise MCP server:

Example 1: Basic Company Information

Prompt: "What is the company name and where is it located?"

Expected Tools Called:

list_naise_companies

Expected Output: Company name and full address (e.g., "MCP Test Company, located at 200 E Santa Clara St, Suite 200, San Jose, CA 95113")

Use Case: Quickly retrieve company details for reports or verification purposes. Note that list_naise_companies returns an array with one company since users can only authenticate to a single company.

Example 2: Employee Department Analysis

Prompt: "How many employees are in each department?"

Expected Tools Called:

list_company_employees
list_company_departments

Expected Output: Breakdown by department (e.g., "Engineering: 6 employees, Sales: 3 employees, Marketing: 2 employees, plus 2 unassigned employees")

Use Case: Understand workforce distribution across departments for planning and resource allocation.

Example 3: Recent Payroll Cost Analysis

Prompt: "What was the total gross payroll cost for the most recent payrolls?"

Expected Tools Called:

list_company_payrolls

Expected Output: Total gross payroll amount (e.g., "$82,527.69 across three recent payroll runs in September-October 2025")

Use Case: Track payroll expenses for budgeting and financial reporting.

Example 4: New Hire Tracking

Prompt: "Which employees were hired since November 1, 2025?"

Expected Tools Called:

list_company_employees

Expected Output: List of recently hired employees with hire dates (e.g., "Maya Angelou (November 7, 2025) and John Lewis (November 14, 2025)")

Use Case: Track recent hires for onboarding workflows and headcount reporting.

Example 5: Compensation Review

Prompt: "Who are the highest and lowest paid employees?"

Expected Tools Called:

list_company_employees

Expected Output: Employees with highest and lowest compensation (e.g., "Highest: Taylor Swift and Regina Spektor ($110,000/year each). Lowest: Isaiah Berlin and Immanuel Kant ($22/hour each)")

Use Case: Review compensation distribution for equity analysis and budget planning.

Example 6: Contractor Management

Prompt: "How many contractors do we have and who are they?"

Expected Tools Called:

list_company_contractors

Expected Output: Count and names of contractors (e.g., "2 contractors: Ella Fitzgerald and Louis Armstrong")

Use Case: Manage contractor relationships and track non-employee workforce.

API Reference

Authentication

The Naise MCP server uses OAuth 2.0 for secure authentication:

Authorization Endpoint: https://naise.app/mcp/oauth/authorize
Token Endpoint: https://naise.app/mcp/oauth/token
Supported Grant Types: authorization_code, refresh_token
PKCE: Required for enhanced security

Available Tools

The Naise MCP server provides 36 tools organized into the following categories:

Company & Organization

list_naise_companies - Get company information for the authenticated account (returns array with one company)
list_company_locations - List all company locations
list_company_departments - List all departments
get_department - Get details for a specific department
get_location - Get details for a specific location

Employees

list_company_employees - List all employees with filtering options
get_naise_employee - Get detailed information about a specific employee
list_employee_jobs - List all jobs for an employee
get_job - Get details for a specific job
list_job_compensations - Get compensation history for a job
get_compensation - Get details for a specific compensation record
list_employee_employment_history - List employment history for an employee
list_employee_terminations - List termination records for an employee
get_employee_rehire - Get rehire details for an employee
list_employee_custom_fields - List custom field values for an employee
list_employee_home_addresses - List home addresses for an employee
get_employee_home_address - Get details for a specific home address
list_employee_work_addresses - List work addresses for an employee
get_employee_work_address - Get details for a specific work address

Contractors

list_company_contractors - List all contractors
get_contractor - Get detailed information about a specific contractor
list_company_contractor_payments - List payment history for contractors
get_contractor_payment - Get details for a specific contractor payment
list_company_contractor_payment_groups - List contractor payment groups
get_contractor_payment_group - Get all payments in a payment group

Payroll

list_company_payrolls - List all payroll runs with filtering (filters by pay period dates, not check dates)
get_payroll - Get detailed information about a specific payroll
list_company_pay_schedules - List all pay schedules for a company
get_pay_schedule - Get details for a specific pay schedule
list_company_pay_periods - List pay periods for a company
list_company_pay_schedule_assignments - List employee-to-pay-schedule assignments
list_company_earning_types - List earning types configured for a company

Time Tracking

list_company_time_sheets - List all timesheets for a company
get_time_sheet - Get details and time entries for a timesheet

Utility

get_token_info - Get OAuth scope and token information
list_company_custom_fields_schema - Get custom field schema for a company

Tool Parameters

All list tools support pagination and filtering:

page (integer): Page number for pagination (default: 1)
per (integer): Results per page (default: 25, max: 100)
include (string): Comma-separated list of fields to include in response

Response Format

All tools return JSON responses following the MCP protocol specification. Successful responses include:

jsonrpc: "2.0"
id: Request identifier
result: Tool execution results

Error responses include:

jsonrpc: "2.0"
id: Request identifier
error: Object containing code, message, and data fields

Rate Limits

The Naise MCP server enforces rate limits to ensure fair usage:

Per User: 100 requests per minute
Per Company: 500 requests per minute

If you exceed rate limits, you'll receive a 429 error with a Retry-After header indicating when you can retry.

Token Efficiency

To minimize token usage and improve performance:

Use pagination parameters (page, per) to limit result sets
Use the include parameter to request only needed fields
Filter results using available query parameters (e.g., hired_after, department_id)
Cache frequently accessed data when possible

Troubleshooting Guide

Connection Issues

Problem: "Unauthorized" error

Solution:

For Cursor:

Go to "Cursor Settings" → "Tools & Integrations"
Under "MCP Tools," find "naise-mcp"
Click "Log out" next to the server
Click "Needs login" to log back in and reauthorize

For Claude:

Go to Settings → Connectors
Find the Naise connector
Click the ellipsis (...) and select "Disconnect"
Click "Connect" to reconnect and reauthorize
If you click "Configure" and no tools show up, follow the disconnect and reconnect steps above

Problem: "Failed to connect to Naise MCP server"

Solution:

Verify you're using the correct URL: https://naise.app/mcp
Check your internet connection
Try disconnecting and reconnecting the server
Clear your browser cache and cookies
If using Cursor, toggle the server off and back on

Problem: "Authentication failed" or "Invalid credentials"

Solution:

Ensure you're logged into the correct Naise account
Clear cookies and try authenticating again
Verify you have admin access to the company you're trying to connect
Check if your Naise session has expired - log in again
For demo environments, ensure you're not logged in as a super user

Problem: "No companies available" after authentication

Solution:

Verify your Naise account has at least one company
Ensure you have admin access to at least one company
Try logging out of Naise completely and reconnecting
Contact Naise support if you believe you should have access

Tool Execution Issues

Problem: Tools are not appearing or not being called

Solution:

Confirm the MCP server is active in your client's tool list
Check that you've granted the appropriate data permissions during OAuth
Try opening a new chat/conversation
Verify your subscription level supports MCP (Pro/Max for Claude, Pro+ for Cursor)
Review your prompt - be specific about what data you need

Problem: "Permission denied" or "Insufficient scope" errors

Solution:

Disconnect and reconnect the server
During reconnection, ensure you select all necessary data categories
Verify the company you connected has the relevant data (e.g., payroll data exists)
Check if your Naise user role has access to the requested data type

Problem: Tool returns empty results or "No data found"

Solution:

Verify the data exists in your Naise account (log in directly to check)
Check date ranges - you may be querying outside available data
Review filter parameters - they may be too restrictive
Try broadening your query or removing filters
For payroll data, ensure payrolls have been processed

Response Quality Issues

Problem: LLM provides incorrect or incomplete answers

Solution:

Always verify tool calls before execution - the LLM may have selected wrong tools
Review the raw tool response data to confirm accuracy
Rephrase your prompt to be more specific
Break complex queries into smaller, sequential questions
Explicitly mention which company or date range you're interested in
Ask the LLM to show you which tools it plans to call before executing

Problem: LLM hallucinates data not in the response

Solution:

Ask the LLM to cite which tool response contains the information
Request raw data/JSON responses to verify
Explicitly instruct: "Only use data from tool responses, do not make assumptions"
Break down your question into multiple specific queries
Always verify critical information directly in Naise

Problem: Response times are slow

Solution:

Reduce the scope of your query (limit date ranges, employee counts, etc.)
Use pagination to request smaller result sets
Ask about specific entities rather than broad "all employees" queries
Check Naise API status (status.naise.app)
Try your query during off-peak hours

Error Messages

Error: "Rate limit exceeded"

Message: "You have exceeded the rate limit. Please try again later."

Solution:

Wait for the time period specified in the error message
Reduce the frequency of your requests
Batch multiple questions into a single conversation
Use pagination instead of requesting large datasets at once

Error: "Tool not found"

Message: "The requested tool does not exist"

Solution:

Verify you're using a supported tool name (see API Reference)
Ensure you've granted permissions for that data category
Try disconnecting and reconnecting the server
The tool may have been renamed - check the latest documentation

Error: "Invalid parameters"

Message: "One or more parameters are invalid"

Solution:

Review the tool's parameter requirements in API Reference
Check date formats (ISO 8601: YYYY-MM-DD)
Verify numeric parameters are valid
Ensure required parameters are provided
Remove any unsupported parameters

Error: "Session expired"

Message: "Your authentication session has expired"

Solution:

Disconnect and reconnect the MCP server
Log in to Naise again
Clear your browser cache and cookies
Re-authenticate through the OAuth flow

Best Practices for Reliable Results

Start Simple: Begin with basic queries before attempting complex analysis
Verify Data: Always check that the tool responses contain the data you expect
Be Specific: Include company names, date ranges, and specific identifiers in prompts
Sequential Queries: For complex questions, break them into steps
Manual Confirmation: Never enable automatic tool execution
Isolated Sessions: Use Naise MCP alone, don't mix with other MCP servers
Regular Reconnection: If you experience issues, try disconnecting and reconnecting
Check Permissions: Ensure you've granted all necessary OAuth scopes

Getting Additional Help

If you continue to experience issues:

Documentation: Review this documentation and the MCP specification
Status Page: Check https://status.naise.app for service interruptions
Support Contact: Email support@naise.app with:
- Detailed description of the issue
- Steps to reproduce
- Error messages (if any)
- Timestamp of the issue
- MCP client and version you're using
Privacy Policy: https://naise.app/legal/privacy
Terms of Service: https://naise.app/legal/terms/naise-mcp

Data Privacy & Security

What Data is Collected

When you use the Naise MCP server, we collect:

Tool call logs: Tool name, parameters (sanitized), timestamp, request ID
Authentication data: OAuth tokens, refresh tokens, company ID
Usage metadata: Request counts, error rates, response times

What Data is NOT Collected

We do NOT log:

Full conversation history
Personally identifiable information (PII) beyond what's necessary for authentication

Data Retention

Tool call logs: Retained for 90 days for debugging and compliance
OAuth tokens: Stored securely, refreshed automatically, revoked on disconnect
Usage metrics: Aggregated and anonymized after 30 days

Your Rights

You have the right to:

Submit a request to exercise your privacy rights
Export your tool usage logs
Revoke access at any time by disconnecting the MCP server
Review OAuth permissions and modify scope selections

For data privacy requests, contact: privacy@naise.app

Technical Details

Protocol Version

MCP Protocol: 2025-06-18
Transport: Streamable HTTP (POST requests)
Authentication: OAuth 2.0 with PKCE

Server Information

Name: Naise MCP Server
Version: 0.1.0
Privacy Policy: https://naise.app/legal/privacy
Terms of Service: https://naise.app/legal/terms/naise-mcp
Support: support@naise.app
Support URL: https://support.naise.app/mcp

Service Level Agreement (SLA)

Uptime: 99.9% monthly uptime target
Support Response: Within 1 business day for critical issues
Performance: 95th percentile response time < 2 seconds

Note: AI platforms referenced for illustrative purposes only; Naise MCP is not affiliated with or endorsed by any AI platforms.

This documentation is current as of November 2025. For the latest updates, visithttps://docs.naise.app/mcp

Demo & Testing Guide

Naise MCP Server - Demo & Testing Guide

This guide is for testing the Naise MCP server using demo companies. Use this before connecting your production company data.

Prerequisites

Demo Naise company with sample data
Claude: Claude Pro or Max subscription
Cursor: Cursor Pro, Pro+, Ultra, Teams or Enterprise
Gemini: Gemini CLI installed

Test Account Credentials

For standardized testing, use the following demo account:

Email: naise.demo@gmail.com
Password: TestPassword1!
Company Name: MCP Test Company

This account provides access to a pre-configured demo company with sample employee, contractor, and payroll data.

Demo Environment Setup

Claude

Within the Claude interface, click your avatar in the bottom left corner
Click "Settings"
Click "Connectors" in the left nav
Click "Add custom connector"
Input "Naise" as the "Name"
Input the following as the Remote MCP server URL: https://naise.app/mcp
Click "Add"
Click the ellipses (...)
Click "Disconnect"
Confirm the disconnection by clicking "Disconnect" within the modal
Click "Connect"
- Note: If you have an active super user session in demo, you'll first need to log out or clear your cookies
Log in using the test account credentials (see Test Account Credentials section above)
You'll see "MCP Test Company" displayed (this is the only company for the test account)
Click "Authorize"
Open up a new chat
Confirm the Naise MCP server is active via the settings dropdown, which is found to the left of the "Research" button
Begin testing!

Cursor

Within the Cursor IDE, go to "Cursor" (in the menu bar) → "Cursor Settings"
Click "Tools & Integrations"
Under "MCP Tools," click "New MCP Server"
Input the following into the automatically generated mcp.json file:

JSON

{

"mcpServers": {

"naise-mcp-demo": {

"url": "https://naise.app/mcp /"

}

Save the updated file
Click "Needs login" under "naise-mcp-demo"
- If under "naise-mcp-demo" it says "Loading tools," toggle the switch off and back on
Click "Open"
- Note: If you have an active super user session in demo, either clear your cookies or open the link manually in an Incognito window
Log in using the test account credentials (see Test Account Credentials section above)
You'll see "MCP Test Company" displayed (this is the only company for the test account)
Click "Authorize"
Click "Open Cursor"
- If prompted to "Allow 'cursor-retrieval' extension to open this URI?" click "Open"
Within the "AI Pane," open up a New Chat
Within the new chat, use the following introductory prompt and begin testing:
- Limit this chat to MCP: 'naise-mcp-demo'

Gemini CLI

Prerequisites: Gemini CLI must be installed (installation instructions)

Add the following to your Gemini settings.json file, which can be found within the .gemini folder:

JSON

{

"mcpServers": {

"naise-demo": {

"httpUrl": "https://naise.app/mcp"

}

Start the tool using gemini
Authenticate using one of the methods provided
Input /mcp auth naise-demo
- Note: If you have an active super user session in demo, you'll first need to log out or clear your cookies
Log in using the test account credentials (see Test Account Credentials section above)
You'll see "MCP Test Company" displayed (this is the only company for the test account)
Click "Authorize"
Confirm the MCP server is connected and ready by inputting /mcp list
Begin testing!

Expected Test Data

When you log in with the test account credentials, you'll have access to a company called "MCP Test Company" with the following sample data:

Company Details

Display Name: MCP Test Company
Location: 200 E Santa Clara St, Suite 200, San Jose, CA 95113
Departments: Engineering (6 employees), Sales (3 employees), Marketing (2 employees)
Total Employees: 13 (11 assigned to departments, 2 unassigned)
Total Contractors: 2
Pay Schedule: Every other Friday (bi-weekly)

Sample Employees

Engineering Department:

Taylor Swift - CTO, $110,000/year
Regina Spektor - CEO, $110,000/year
Friedrich Nietzsche - Engineer, $80,000/year
Arthur Schopenhauer - Engineer, $88,000/year
Alexander Hamilton - Marketing Director, $78,000/year
Immanuel Kant - Client Support Manager, $22/hour

Sales Department:

Patricia Churchland - Account Director, $78,000/year
Isaiah Berlin - Client Support Manager, $22/hour
Ammie Purdy - Office Administrator, $37/hour

Marketing Department:

Soren Kierkegaard - Client Support Director, $70,000/year
Hannah Arendt - Account Manager, $61,000/year

Unassigned:

Maya Angelou - Chief Editor, $85,000/year (hired November 7, 2025)
John Lewis - Advocate, $85,000/year (hired November 14, 2025)

Contractors:

Ella Fitzgerald - Hourly ($18/hour)
Louis Armstrong - Fixed

Sample Payrolls

Three payrolls have been processed for September-October 2025:

September 26, 2025
- Pay Period: September 6 - September 19, 2025
- Gross Pay: $27,509.23
- Employer Taxes: $3,031.69
- Net Pay: $18,275.02
October 10, 2025
- Pay Period: September 20 - October 3, 2025
- Gross Pay: $27,509.23
- Employer Taxes: $2,936.00
- Net Pay: $18,275.03
October 24, 2025
- Pay Period: October 4 - October 17, 2025
- Gross Pay: $27,509.23
- Employer Taxes: $2,425.44
- Net Pay: $18,275.05

Test Scenarios

Use these test scenarios to validate MCP functionality:

Test 1: Basic Information Retrieval

Prompt: "What is the company name and where is it located?" Expected Result: "MCP Test Company, located at 200 E Santa Clara St, Suite 200, San Jose, CA 95113"

Test 2: Department Analysis

Prompt: "How many employees are in each department?" Expected Result: "Engineering: 6 employees, Sales: 3 employees, Marketing: 2 employees"

Test 3: Payroll Cost Analysis

Prompt: "What was the total gross payroll for all payrolls in September-October 2025?" Expected Result: "$82,527.69 (three payrolls of $27,509.23 each, with check dates September 26, October 10, and October 24, 2025)"

Test 4: New Hire Tracking

Prompt: "Which employees were hired since November 1, 2025?" Expected Result: "Maya Angelou (November 7, 2025) and John Lewis (November 14, 2025)"

Test 5: Compensation Analysis

Prompt: "Who are the highest and lowest paid employees?" Expected Result: "Highest: Taylor Swift and Regina Spektor ($110,000/year each). Lowest: Isaiah Berlin and Immanuel Kant ($22/hour each)"

Test 6: Contractor Information

Prompt: "How many contractors do we have and who are they?" Expected Result: "2 contractors: Ella Fitzgerald and Louis Armstrong"

Test 7: Employee Details

Prompt: "What is Patricia Churchland's job title and annual salary?" Expected Result: "Account Director, $78,000/year"

Test 8: Payroll Trend Analysis

Prompt: "How has the gross payroll changed across the three most recent payrolls?" Expected Result: "It has remained consistent at $27,509.23 for all three payrolls"

Test 9: Tax Analysis

Prompt: "What is the trend in employer tax payments across the three most recent payrolls?" Expected Result: "Decreasing: $3,031.69 (September 26) → $2,936.00 (October 10) → $2,425.44 (October 24)"

Test 10: Department Distribution

Prompt: "Which employees in Marketing have salaries over $60,000?" Expected Result: "Soren Kierkegaard ($70,000/year) and Hannah Arendt ($61,000/year)"

Test 11: Multi-Turn Conversation

Turn 1: "Show me all departments" Expected: "Sales, Marketing, and Engineering"

Turn 2: "Which one has the most employees?" Expected: "Engineering with 6 employees"

Turn 3: "What's their average salary?" Expected: "Approximately $93,200 per year for salaried employees (Taylor: $110k, Regina: $110k, Friedrich: $80k, Arthur: $88k, Alexander: $78k)"

Test 12: Unassigned Employees

Prompt: "Which employees are not assigned to any department?" Expected Result: "Maya Angelou (Chief Editor) and John Lewis (Advocate), both hired in November 2025"

Validation Checklist

After completing your tests, verify:

All tool calls returned expected data
No authentication or permission errors occurred
Multi-turn conversations maintained context appropriately
Numeric calculations were accurate
Date filtering worked correctly
Employee/contractor data was retrieved accurately
Payroll data matched expected values
Department information was correct
Unassigned employees were properly identified
Error handling was appropriate for invalid queries
Response times were acceptable (< 5 seconds per tool call)

Common Demo Issues

Issue: Super User Session Conflicts

Symptom: Cannot authenticate as company admin Solution: Clear cookies or use incognito/private browsing mode

Issue: Demo Company Not Found

Symptom: "No companies available" after auth Solution: Verify you're logging in with the correct admin credentials

Issue: Empty Payroll Results

Symptom: Queries for specific date ranges return no payrolls Solution: The demo company has payrolls from September-October 2025. Adjust your date filters accordingly.

Issue: Outdated Data

Symptom: Employee counts or names don't match expected values Solution: Demo company may have been modified. Refer to the Expected Test Data section in this guide for the current baseline configuration.

Demo Data Refresh

If demo data becomes stale or inconsistent:

Record current test results
Reset demo company to baseline configuration
Re-run all test scenarios
Compare results to expected outcomes
Document any discrepancies

Transitioning to Production

Once testing is complete with demo data:

Disconnect the demo MCP server
Clear any cached authentication
Follow production setup instructions
Connect to https://naise.app/mcp
Authenticate with your production Naise account
Start with simple queries to verify connection
Gradually increase complexity as confidence builds

Important: Demo environment is for testing only. Do not use production credentials in demo or demo credentials in production. Do not add production data to the demo environment.

Changelog

Updated about 2 months ago

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