How to Build Custom Front Integrations With No Native App (2026)

Front's rules are excellent at moving conversations around — routing, tagging, assigning, snoozing — but a rule can't reason over a live lookup or write to a system it has no connector for. So the moment a customer asks "where's my order?" or "cancel my subscription," an agent is back to opening another tab.

The good news: a missing App Store integration is no longer a dead end. If the tool you need has an API, you can connect it to Front yourself — without publishing an app, and without writing integration code. This guide shows how, using AI-agent Custom Tools.

First, the framing. Macha isn't a Front replacement — it runs on top of the Front shared inbox you already use. Your team keeps working in Front, with its comments, @mentions, and rules; Macha adds an AI layer that can read conversations, reason, and — through Custom Tools — reach into any other system to answer or act.

What "custom integration" actually means now

For years, "integrating X with Front" meant one of two things: find a pre-built App Store integration, or pay a developer to build one against Front's API and the target tool's API. Both are heavy. An App Store integration is someone else's idea of the integration — and often read-only; a bespoke one is a project with a maintenance tail.

A Custom Tool is a third path. Instead of building an integration, you define an action — "look up an order," "create a Jira issue," "check a subscription in our billing system" — and point it at the relevant API endpoint. Your Macha AI agent then calls that action while it works a conversation, passes the right parameters, and reasons over what comes back. No App Store listing, no review, no glue code.

The difference in practice is control. A native integration does what its author decided it should do — usually show you something. A Custom Tool does exactly what you describe, including taking an action, scoped to the one job you need.

The model in three steps

Every Custom Tool follows the same shape, whether it's wrapping Salesforce, a Postgres database, or an internal microservice.

1. Point it at the API. You give Macha the endpoint, method, and credentials. If you'd rather not fill in a form, the built-in Sidekick will scaffold the whole thing from a plain-English description — "connect Stripe to look up payments," "hook up our internal orders API."

2. Define the action. Give the tool a label and a description the AI uses to decide when to call it, set the method and URL (with placeholders like {{order_id}} for the parameters the agent will fill), and choose whether it's a Read or a Write. Reads are safe lookups; Writes — refunds, status changes, record updates — require confirmation before they run. Authentication, static headers, and response mapping are all here too, so a real production endpoint drops straight in.

3. The agent uses it live. Once the tool exists, your agent calls it mid-conversation. A customer asks "where's my order?" in a Front inbox; the agent recognizes the intent, calls Get Order Status with the order ID it pulled from the thread, and answers with the real status and tracking — grounded in your system of record, not a guess.

That's the entire loop: define once, and the AI decides when to use it on every relevant conversation thereafter.

What it looks like once you've built a few

Custom Tools aren't a one-off escape hatch — teams build a small library of them, grouped by the service they wrap. Here's a Macha workspace with tools for Postmark (list templates, send email) and a store's order-lookup endpoint, each tagged Read or Write with its API URL.

Notice the mix of GET/Read and POST/Write. A teammate can be allowed to look up anything but only act — send, refund, update — with a confirmation step. That boundary is enforced per tool and per agent.

Read vs Write, auth, and staying safe

Because a Custom Tool can reach into real systems, the guardrails matter as much as the capability:

• Read vs Write. Read tools are free to call. Write tools (anything that changes state) require confirmation, so an agent can't silently issue a refund or delete a record.
• Scoped by design. A tool exposes exactly one action against one endpoint. It does the job you defined and nothing else.
• Permissioned per agent. You decide which agents get which tools — your triage agent might only read; a senior-support agent might be allowed to write.
• Audited. Every call is logged, so you can see exactly what ran, with what inputs, and when.

For authentication, the builder supports the common patterns (API keys, bearer tokens, custom headers), so tools that need credentials — most of them — work without exposing secrets in the conversation.

When to use an App Store integration vs a Custom Tool

Custom Tools don't make the Front App Store obsolete; they cover what it can't.

• Reach for an App Store integration when a well-maintained one already exists for a mainstream tool and does what you need out of the box — a CRM sidebar, calendar, or messaging connector. If Macha has a native connector for it, use that (it's deeper and zero-setup).
• Reach for a Custom Tool when there's no integration, the one that exists only shows data, the tool is internal or industry-specific, or you need a specific action from the conversation. This is most real workflows.

The honest rule of thumb: if you've ever said "I wish Front could just check X for me," and X has an API, that's a Custom Tool.

Examples worth building

The pattern generalizes across every category of tool a support team touches:

• CRM — pull a customer's account, plan, and owner from Salesforce or HubSpot into the conversation.
• Databases & warehouses — query orders, subscriptions, or usage from Postgres, Snowflake, or BigQuery to answer from source of truth.
• Billing & payments — check a subscription or issue a refund in Chargebee, Recurly, or Stripe.
• Engineering — open a Jira, Linear, or GitHub issue from a bug report and read its status back.
• Internal systems — hit your own admin API to look up an account, reset a flag, or trigger a job.

For a browsable list of tools you can connect this way — 200+ across CRM, databases, e-commerce, ITSM, and more — see the Custom Tools integration directory. If it has an API, it belongs on that list.

Running more than one help desk? The same approach works on Zendesk, Freshdesk, Intercom, and Gorgias — Custom Tools are portable across all of them.

The bottom line

A missing App Store integration used to mean "not supported." With Custom Tools, it means "not yet — give me ten minutes." You describe the action, point it at the API, and your Front AI agents can read and write it live inside a conversation, with Read/Write guardrails, per-agent permissions, and a full audit trail. The integration you need stops being something you wait for and becomes something you build.

Ready to try it? See how Custom Tools work, browse the integration directory, or start a free trial and wire up your first tool today.

Frequently asked questions

Do I need an engineer to build a Custom Tool for Front? No. You can describe the integration in plain English and Macha's Sidekick scaffolds the request, authentication, and parameters. Technical teams can go deeper with full control over methods, headers, bodies, and response mapping.

Is this a Front App Store integration? No — and that's the point. A Custom Tool doesn't need an App Store listing or review. It's an action your AI agent calls against any API, so you can connect tools that will never have a native integration, including internal and industry-specific systems.

Front already shows customer data in a sidebar — how is this different? Sidebar integrations mostly display data. A Custom Tool lets your AI agent use an API from the conversation — fetch a live lookup or take an action like a refund or update — and reason over the result in its reply.

Can it change data, or only read it? Both. Read tools are safe lookups; Write tools (refunds, updates, status changes) require a confirmation step before they run, and you control which agents can use them.

Is it secure? Yes. Custom Tools are scoped to a single action, permissioned per agent, and every call is audited — so you always know what ran, with what inputs, and when.