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AssetFit is an asset management platform used to track, maintain, and optimize physical assets across their lifecycle. With Makini's MCP server, AI agents connect to AssetFit data and workflows from day one, without writing any integration code.
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AssetFit is a mobile first CMMS for small maintenance teams, covering work orders, asset tracking, preventive maintenance schedules, spare parts and inspection checklists on iOS, Android and the web. Its status is uncertain: the vendor site getassetfit.com was unreachable when we checked in October 2026, one software catalog lists the product as discontinued, and catalogs disagree about the company behind it. If you still run AssetFit, confirm support before planning new work on it.
AssetFit never published a public developer API: the catalogs that list the product either say no API is provided or leave the field empty, and we found no developer documentation from the vendor. That shapes any integration, since reading AssetFit data has to work through the access a normal user has. Makini connects with the login you already use, and get_connection_details shows which AssetFit objects and fields that particular connection exposes.
Yes, Makini offers an MCP server for AssetFit: you sign in to AssetFit through Makini Link, Makini issues an MCP endpoint, and you paste it into Claude, ChatGPT, Cursor or another MCP client. Because AssetFit's own status is uncertain and it has no documented public API, run get_connection_details right after connecting to see which objects, such as work orders, assets or stock items, this connection actually exposes before building anything on it.
AssetFit schedules preventive maintenance as recurring tasks on each asset, assigns them to technicians and keeps completed work in the asset's maintenance history, next to inspection checklists that replaced paper forms and spreadsheets. Spare parts are tracked as an inventory list so a technician can record what a repair consumed. Field names and the exact set of modules depend on the plan the account was on, so check before assuming a feature exists.
Call get_connection_details on your AssetFit connection; it lists the objects and fields that connection exposes to the agent, for example work orders, assets, locations or stock items where supported. Do this before asking the agent for reports, because a small CMMS like AssetFit may expose fewer fields than Makini's unified models allow, and custom fields or inspection answers may not be among them. Compare the list with what your team actually uses in the app.
No, keep an AI agent on reading AssetFit while the product's future is uncertain: have it find overdue preventive tasks or repeat failures on one asset, and avoid building a workflow that depends on writing to a system that may be withdrawn. Makini's tool list includes create and update tools for work orders; where the connection and the user's rights allow it, a draft work order for a supervisor to review is the sensible limit.
The AssetFit login that authorizes the connection in Makini Link sets the ceiling: the agent sees only the assets, work orders and parts that user can see, so use a maintenance manager or administrator account rather than a single technician. The plan matters too, since catalogs list AssetFit with a free tier and paid per user plans with different features. Credentials are entered in Makini Link, and the endpoint is scoped to that login.
An AI agent can read AssetFit work orders, assets and parts through the MCP connection and summarize them into the structure a new CMMS expects: the asset list, open and completed work orders, preventive schedules and parts consumed. Do this while the AssetFit account is still active, since a discontinued product can disappear with its data. Keep the export reviewable, and load the new system through its own import tools, not through agent writes.