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Overview

Softr Agents let you build an AI assistant that holds a conversation, follows your instructions, and takes real actions across your apps, databases, and connected services. You don’t script every step. You describe what the agent is for and give it tools. The agent decides which tools to use, and in what order, to answer a question or finish a task. An agent can:
  • Chat with your app users and respond in natural language.
  • Search a knowledge base you upload (files or links) to give grounded answers.
  • Take actions: read and write records in your data sources, send emails or Slack messages, search the web, and call external services.
  • Remember relevant details about a user across the conversation.
  • Run on a schedule, unattended, to handle recurring work.
Agents and Database AI Agents. This page covers standalone Agents: assistants you connect to your apps or run on a schedule. They differ from Database AI Agents, which auto-fill and enrich individual fields in a Softr Database table. The two work well together.

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Agent types

When you create an agent, you first choose how it runs. This can be changed later.
  • App agent: Users chat with this agent from selected apps. Use it for support assistants, in-app helpers, and anything a person talks to directly.
  • Scheduled agent: Runs on a recurring schedule, with no live user. Use it for recurring reports, data cleanup, sync jobs, and other background tasks.
The Choose an agent type dialog with App agent and Scheduled agent

The Choose an agent type dialog

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The app as context for an App agent

When you connect an App agent to a Softr app, the app becomes a source of tools and data for the agent, the same way the App MCP Server exposes an app to external AI assistants. The agent reads and acts on your app’s data as the signed-in user who chats with it. It never acts as an admin or as the app itself. So the agent can only do what that user can already do in the app:
  • The blocks you build decide what’s possible. A list, grid, or table lets the agent read records. A form lets it create records (only the fields the form shows). A profile or inline editing lets it update. A delete action lets it delete.
  • If no block shows a table, the agent can’t touch that table, even if the data source contains it.
  • User groups, page visibility, and data restrictions still apply. Each user sees the same records and actions through the agent as they see in the app.
To widen or narrow what an App agent can do, change what the app shows. Add a form to allow record creation, add a list to allow reading, or restrict a block by user group to limit access. See App MCP Server for the full model of how an app exposes its data.

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Step-by-step: Create your first agent

1

Create an agent

From your Softr dashboard, open Agents in the left sidebar. Click Create, or Create your first agent if you have none yet.
The Agents page with six agent cards, each marked Live or Draft

The Agents page lists every agent in your workspace

2

Choose an agent type

In the Choose an agent type dialog, pick App agent (users chat with it from your apps) or Scheduled agent (runs on a recurring schedule). Click Next. You can switch types later in the agent’s configuration.
3

Set up the agent profile

In the editor, give your agent a title and set up its profile:
  • Model: Choose the AI model that powers the agent. Models are grouped by cost, so you can balance capability and price (see Choosing a model).
  • Reasoning effort: For models that support it, choose how much the model thinks before it answers: Off, Low, Medium, or High. Higher effort gives better results on complex tasks, but it is slower and costs more.
  • Instructions: Describe how the agent behaves and responds. State its goal, what it must always do, and what it must never do.
The agent editor with frames around Connected apps, Tools, Knowledge, and Instructions

The agent editor: connected apps, tools, knowledge, and instructions

4

Connect it to your apps or add a schedule

Depending on the agent type:
  • App agent: In the Connected apps card, click the + button to choose the Softr apps where the agent is available. You can Test the agent in each connected app.
  • Scheduled agent: In the Schedules card, click the + button to create a recurring schedule. Set the frequency and a timezone. You can also add a message that starts each run.
The Connect apps dialog listing the apps in the workspace

The Connect apps dialog

The Add schedule dialog with frequency, time, and weekends

The Add schedule dialog

5

Add tools

In the Tools card, click the + button to choose what the agent can do, such as read and write records in a data source, send an email, or post to Slack. Set each tool’s authentication. You can also require confirmation before the tool runs. See Tools & actions.
The Choose a tool window with categories, Softr and built-in tools, and integrations

The tool picker: Softr and built-in tools, and integrations

6

Add knowledge (optional)

In the Knowledge card, click the + button to upload files or insert links the agent can search when answering. See Knowledge.
The Add knowledge dialog with Upload file and Insert link

The Add knowledge dialog

7

Test and turn it on

Use the Test agent panel on the right to run the agent and watch its responses and tool calls. When you’re happy, enable the Agent enabled toggle and click Turn on to publish it. If you edit a published agent, a banner tells you that your draft differs from the live version. Click Update to publish your changes.
The Test agent panel with two tool calls and a streamed answer

The Test agent panel shows the tool calls and the answer

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Choosing a model

Softr offers models from several providers, grouped by cost tier. Pick based on the task:
Start with a balanced model. Move up to a flagship model only if the agent struggles with multi-step reasoning. A lightweight model keeps costs down for simple, repetitive tasks.
Bring your own key (BYOK). On higher plans, you can use your own LLM provider API key. Your provider account then bills the agent usage, and it doesn’t use Softr AI credits.

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Tools & actions

Tools are the capabilities an agent can use when it responds. Actions are tools tied to a specific integration, such as “Slack: send channel message” or “Google Sheets: create row.” Native actions include:
  • Softr: Read, create, update, and delete records.
  • Google Sheets: Read, create, update, and delete rows.
  • HubSpot: Read, create, update, and delete objects (for example contacts and deals).
  • Gmail: Send emails and create drafts.
  • Slack: Send channel messages, send direct messages, and find users.
  • Send email: Send an email with Softr’s built-in email service.
Airtable, Notion, and monday.com connect through a predefined MCP server, not through individual actions. Connecting one gives the agent all the tools of that service. Other data and productivity services (Attio, Apollo, Supabase, Linear, and more) are available the same way.
When you add a tool, you configure:
  • Authentication: Choose Per user authentication (uses each user’s own account or permissions) or Shared authentication (uses one shared account or connection).
  • Ask for confirmation: When on, the agent shows a summary and waits for the user’s approval before it runs the action. Scheduled agents don’t have this option, because they run without a live user.
  • Configure input fields: For each field, choose Agent decides (the agent fills it in at run time) or Custom (you set a fixed value the agent can’t change).

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Connecting an MCP server

Agents can connect to external tool servers through the Model Context Protocol (MCP) to get more tools. Connect a predefined MCP server in a few clicks, or add a Custom MCP server with your own URL.

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Predefined MCP servers

Softr offers ready-made connections with the server URL already set. You only authenticate. They include:
  • Softr Databases: Read and manage your database tables.
  • Airtable: Read and manage bases, tables, and records.
  • Notion: Search and edit pages and databases.
  • monday.com: Manage boards, items, and updates.
  • Attio: Manage CRM records, lists, and notes.
  • Apollo: Search contacts and enrich leads.
  • Brevo: Manage contacts and email campaigns.
  • Calendly and Cal.com: Schedule and manage bookings.
  • Fathom and Granola: Access meeting recordings, summaries, and notes.
  • Linear: Manage issues, projects, and cycles.
  • Supabase: Query and manage your database.
  • Clay: Enrich and research data.
  • Apify: Run scrapers and automation actors.
  • Replicate: Run and manage AI models.
  • Atlassian: Work with Jira issues and Confluence pages.
Pick a predefined server, authorize it, and choose which of its tools the agent can use.
A native tool (see Tools & actions) gives the agent one narrow action with control per field. A predefined MCP server gives the agent all the tools of a service at once. Choose native actions to limit exactly what the agent can do. Choose MCP for broader access.

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Custom MCP server

To connect your own MCP server, provide:
  • Name: A label for the server, such as “Internal knowledge base”.
  • Server URL: The MCP server endpoint.
  • Authentication: OAuth, Headers (for example an Authorization header), or none.
For each tool the server exposes, set a permission:
  • Allow: Always allow the call, with no prompt.
  • Ask: Require user approval before the call runs. Scheduled runs approve the call automatically.
  • Deny: Never allow the call. The agent doesn’t get the tool.
Write actions (those that change data) require approval by default. Read-only tools are safer to allow. Review the permissions before you turn the agent on.

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Knowledge

Add files or links the agent can search when answering. Softr indexes uploaded files (PDF, TXT, MD) and links, so the agent can find and cite relevant passages. Each source has a status while Softr processes it:
  • Pending, then Indexing, then Ready: the agent can search the source.
  • Failed: indexing didn’t finish. Remove the source and add it again.
Knowledge grounds an agent in your own content, such as product docs, policies, and FAQs. The agent answers from your material instead of guessing.

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Testing & runs

Use the Test agent panel to run the agent and watch it work: its streamed response, the tools it calls, and the tasks it plans. Open the Runs panel to review every run. Each run records:
  • Model and Provider
  • Duration and Tool calls
  • Credits charged and Token usage (input, cached, output, total)
  • Finish reason, plus a Run failed badge and a Show errors only filter for troubleshooting
A successful run with its model, duration, tool calls, and the transcript

A run with its details and transcript

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Pricing and credits

Agent runs use AI credits. The credits a run uses depend on the model, the number and size of tool calls, knowledge search, and output length. Every Softr plan, including Free, comes with a monthly amount of AI credits. If you use them all, AI features pause until your credits reset with your plan or you add more with a credit add-on. On higher plans, you can also bring your own API key, so your provider bills the usage. Learn more about AI credits

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FAQ

Agents (this page) are standalone AI assistants. They chat with your users or run on a schedule, and they take actions across your apps, data sources, and connected services.Database AI Agents work inside a Softr Database table. They auto-fill, tag, summarize, or enrich individual fields when records are created or updated.Both use AI credits, and you can use them together. For example, a Database AI Agent classifies a record, and a standalone Agent follows up based on that value.
No. You set up agents visually: pick a model, write plain-language instructions, add tools and knowledge, and turn the agent on. A custom MCP server is optional. You only need it to give the agent your own external tools.
Yes. Create an App agent and connect it to one or more Softr apps. Your users then chat with it inside the app. You choose the apps where it appears.
Yes. Create a Scheduled agent and add a recurring schedule with a timezone. It runs unattended on that schedule. Use it for reports, cleanup, and sync jobs.
Yes. Add a Custom MCP server, or pick a predefined one, to give the agent external tools through the Model Context Protocol. You set an Allow, Ask, or Deny permission for each tool.
Start with a balanced mid-tier model. Move up to a flagship model for demanding multi-step reasoning. Move down to a lightweight model for simple, high-volume tasks. See Choosing a model.
Agent runs use AI credits, which every plan includes. Usage depends on the model, tool calls, knowledge search, and output length. On higher plans you can bring your own API key. Learn more about AI credits