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Jobber MCP Server

Connects AI clients to Jobber for client, job, invoice, and quote workflows.

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Install Jobber MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "jobber-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "jobber-mcp-server"
      ],
      "env": {
        "JOBBER_ACCESS_TOKEN": "YOUR_VALUE_HERE",
        "JOBBER_CLIENT_ID": "YOUR_VALUE_HERE",
        "JOBBER_CLIENT_SECRET": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

The install command installed and started the server, which then stopped for configuration (such as an API key) that our sandbox does not have — expected for servers that connect to your account.

npx -y jobber-mcp-server

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 5d ago.

Overview

The jobber-mcp-server MCP server connects MCP-compatible AI clients to Jobber field-service data through a typed API. It provides tools for finding clients, reviewing jobs and invoices, and creating quotes, with OAuth credentials supplied through environment variables. Use it for natural-language operational lookups or quote creation, or enable mock mode to test without a Jobber account.

Use cases

  • Look up client contact details and recent jobs
  • Review invoices by client or payment status
  • Inspect assigned jobs and schedules
  • Create quotes with client line items
  • Test MCP workflows with generated mock data

Key features

  • Client search and lead filtering
  • Client details with recent jobs
  • Job status, schedule, assignee, and line items
  • Invoice filtering and payment details
  • Quote creation with line items
  • Optional mock mode

Tools6

What Jobber MCP Server lets your agent do. Expand a tool for its parameters.

Self-reported~94 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

Not checked yetLast checked 2d ago

We have not completed a health check for this listing yet.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 16d ago via OSV.dev · jobber-mcp-server (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

npm downloads84Package downloads in the last 30 days.
Last commit4mo agoMost recent push to the default branch.
Install checkRunsOur sandbox started it; it then asked for an API key or config.
Tools exposed6Callable tools this server registers over MCP.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How Jobber MCP Server works

What jobber-mcp-server MCP server does

The jobber-mcp-server MCP server gives compatible AI assistants access to selected Jobber business records. It covers client searches and details, job information, invoice lists and details, and quote creation. The server is intended for field-service operations where an agent needs to answer questions about customers, schedules, billing, or sales work without requiring a separate dashboard session.

Client tools support optional search, lead filtering, and result limits. A client detail lookup includes contact information and recent jobs. Job lookups return status, assigned staff, scheduling information, and line items. Invoice tools support filtering by client or status, while invoice details include line items and payment status. Quote creation accepts a client and line items.

How it works

The server runs as a Node.js process and communicates with an MCP client. For live Jobber data, it uses Jobber API access configured with OAuth credentials. Credentials are passed through the process environment and are not logged according to the project documentation.

The repository provides six MCP tools: list_clients, get_client, get_job, list_invoices, get_invoice, and create_quote. An AI client can invoke these tools in response to natural-language requests, such as finding overdue invoices or looking up a customer’s recent jobs. Jobber’s GraphQL API typically adds about 200–500 milliseconds of latency, and broader queries may take longer.

Setup and configuration

Install Node.js 18 or newer, then run the package through npx or configure it as a command in an MCP client. A live configuration requires JOBBER_ACCESS_TOKEN, JOBBER_CLIENT_ID, and JOBBER_CLIENT_SECRET. Obtain the client credentials from the Jobber Developer Portal and complete the OAuth process to receive an access token.

The jobber-mcp-server MCP server can also run in mock mode with JOBBER_MOCK_MODE=true. This uses sample clients, jobs, and invoices without making calls to Jobber, so it is suitable for initial testing without an account. In an MCP configuration, place the variables in the server’s env object. Restart the client after changing its configuration.

The README specifically documents use with Claude Desktop, Cursor, Windsurf, and Cline. It also provides development commands for cloning the repository, installing dependencies, building the project, and opening MCP Inspector.

Tools and capabilities

  • list_clients: find clients using optional search terms, lead filters, and limits.
  • get_client: retrieve contact information and recent jobs for a client ID.
  • get_job: inspect job status, assignees, schedule, and line items.
  • list_invoices: filter invoices by client and/or status.
  • get_invoice: inspect invoice line items and payment status.
  • create_quote: create a quote for a client with specified line items.

These capabilities support client research, daily operations checks, invoice follow-up, field-service reporting, and quote preparation. The available tool list does not describe general-purpose record updates or deletion operations.

Limitations and notes

Live use requires a Jobber account with API access and valid OAuth credentials. Access tokens can expire and may need to be refreshed through the Jobber Developer Portal. Mock mode is limited to generated sample data and does not access a real Jobber account.

Use a limit with list_clients when an initial query should return fewer results. The project is released under the MIT license.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Jobber MCP Server

jobber-mcp-server is an MCP server that connects AI assistants to Jobber field-service data. Its main tools list and retrieve clients, inspect job details, list and retrieve invoices, and create quotes with line items. It uses Jobber OAuth credentials for live data and offers mock mode for testing without a Jobber account.

Install it by running it with Node.js 18 or newer through npx, then add the command and required environment variables to your MCP client configuration. The documented package command uses `npx -y jobber-mcp-server`.

It requires `JOBBER_ACCESS_TOKEN`, `JOBBER_CLIENT_ID`, and `JOBBER_CLIENT_SECRET` for live Jobber access. Set `JOBBER_MOCK_MODE=true` instead when testing with generated data and no Jobber account.

Yes, Cursor is named as a supported MCP client in the README. Configure the server command and its environment variables in Cursor, then restart the client after making configuration changes.

Yes, it provides `create_quote` for creating a quote for a Jobber client with line items. The documented tool list does not specify additional quote-management operations.

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