Verified 2026 Canadian payroll math: employer total cost, employee take-home, net-to-gross. Free.
2026 take-home pay for a Canadian employee on regular salary: CPP/QPP (incl. second-ceiling CPP2/QPP2), EI (and QPIP for Quebec), federal and provincial income tax withheld, net pay per year and per pay period. Assumes a full-year employee with basic TD1 claims. Supported: all 13 Canadian provinces/territories.
| Name | Required | Description | Default |
|---|---|---|---|
| province | Yes | Two-letter province/territory code | |
| annual_salary | Yes | Gross annual salary, CAD | |
| pay_frequency | No | Pay frequency for the per-period view (default biweekly) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description handles transparency. Discloses deductions, assumptions, and year (2026). No side effects; it's a calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. Front-loaded with purpose, then assumptions. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description explains return values (net per year and per period). Assumptions and coverage are sufficient for a calculation tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 3 params (100%). Description adds value by connecting parameters to deductions and output frequencies, enhancing meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes take-home pay for Canadian employees, listing specific deductions (CPP/QPP, EI, QPIP, taxes) and outputs (net per year and per period). Siblings are employer_cost and net_to_gross, making this distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states assumptions (full-year employee, basic TD1 claims) and coverage (all 13 provinces). No when-not-to or alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
What a Canadian employee REALLY costs the employer for 2026: gross salary plus mandatory employer-side contributions (CPP + CPP2 + EI at 1.4x; for Quebec: QPP + QPP2 + EI + QPIP + health services fund + labour-standards contribution), with the excluded items (workers' comp, EHT, vacation pay, benefits) disclosed, never silently omitted. Supported: all 13 Canadian provinces/territories. Annual planning figures.
| Name | Required | Description | Default |
|---|---|---|---|
| province | Yes | Two-letter province/territory code where the employee works | |
| annual_salary | Yes | Gross annual salary, CAD |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses what is included (CPP, EI, etc.), what is excluded (workers' comp, EHT, etc.), and that items are never silently omitted. It also specifies the year and province coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative and front-loaded, but slightly verbose. Each sentence contributes value, making it concise overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers inputs, exclusions, and scope thoroughly. However, it lacks explicit output format details (e.g., whether a single number or object is returned), which is useful given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds context (e.g., 2026, annual planning) but does not significantly deepen understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates total employer cost including mandatory contributions, specifies it's for 2026, and lists included/excluded items. It distinguishes from siblings by focusing on employer cost vs employee take-home or net-to-gross.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates use for annual planning figures and specifies supported provinces. However, it does not explicitly state when not to use or compare to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Invert payroll for 2026: start from the take-home pay you agreed with the employee ("$800/week in their pocket") and get the gross salary that delivers it, the employer's true total cost, and the per-period source-deduction remittances (CRA; split CRA vs Revenu Québec for Quebec). Built for household employers (nanny payroll) who agree on take-home pay; CRA's PDOC computes gross→net and does not cover Quebec. Supported provinces: ON, AB, BC, MB, NS, QC.
| Name | Required | Description | Default |
|---|---|---|---|
| province | Yes | Two-letter province code | |
| pay_frequency | Yes | How often that net amount is paid | |
| target_net_pay | Yes | The agreed take-home amount per pay period, CAD |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses the tool's function, outputs (gross, employer cost, remittances), and special handling for Quebec. It does not mention side effects or auth needs, but as a calculation tool, this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, each serving a distinct purpose: core function in the first, context and differentiation in the second. No wasted words, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 required params, no output schema, 2 siblings), the description adequately explains outputs and supported provinces. It lacks details on output format or remittance breakdown specifics, but overall sufficient for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, establishing a baseline of 3. The description adds value by explaining the purpose of target_net_pay as the 'agreed take-home amount' and clarifying the pay frequency and province context, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool inverts payroll from net to gross, specifies the context (household employers, nanny payroll), and lists supported provinces. It effectively distinguishes from the sibling tools by describing its unique reverse calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool (when agreeing on take-home pay) and contrasts with CRA's PDOC. However, it does not explicitly exclude alternatives or differentiate from sibling tools, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
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The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
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Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
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Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
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Add one secure layer between your agents and this server.
Each tool addresses a distinct payroll question: employee take-home, employer total cost, and net-to-gross inversion. No two tools overlap in purpose.
All tool names follow a consistent verb_noun pattern in snake_case (employee_take_home, employer_total_cost, net_to_gross_salary), making the set predictable.
With only 3 tools, the server is tightly scoped to payroll calculations. While more specialized tools could be added, the count matches the narrow domain.
The tool set covers the core payroll math: net pay, employer cost, and conversion. Minor gaps exist (e.g., no tool for adjusting TD1 claims), but the primary workflows are supported.
