Build Apps & AI Agents Without Code

A one-sentence summary

Momen is a full-stack no-code platform that brings the interface, database, backend processes, permissions, APIs, and AI agents together in a single editor, making it suitable for developing functional web applications directly from prototypes.

Users can use Momen to handle both the front-end and back-end tasks, or they can utilize it as a hosted BaaS service, connecting React, Next.js, Vue, or other custom front-ends via the GraphQL Runtime API.

What is Momen?

Momen is provided by Momen Technologies Inc.; it is a development platform that combines No-Code techniques with AI. It not only generates web pages but also handles data models, server-side logic, user authentication, file storage, as well as the resources needed for deployment and operation.

AI Agents represent a premier capability within the platform: they can read project data, invoke APIs, execute Actionflows or other agents, and then return text, structured data, and media results to the page or backend processes. This enables the creation of applications for customer service, content processing, data analysis, booking, and business automation.

Core components of the platform

• Visual interface: Build responsive Web pages using components, canvases, layouts, and data binding.
• Managed database: Define tables, fields, relationships, views, and permissions in the editor.
• Actionflow: Combines database operations, conditions, loops, APIs, code blocks, and AI execution.
• AI Agent: Configure the model, inputs, prompts, context, tools, and output structure.
• Runtime API: Generates GraphQL interfaces for each project, which can be used by custom front-ends and external systems for making calls.
• Identity and permissions: Establish rules for registration, login, role control, and access to project data.
• Deployment and operation: The platform hosts applications and provides domain names, logging services, resources, as well as options for scaling up.
• Code extension: Develop custom code components using React and TypeScript.
• AI development plugin: Allows compatible coding assistants to read and modify the Momen backend configuration via MCP.

Main capabilities of AI Agents

Connect multiple models

The Agent Editor offers pre-integrated models and allows paid services to incorporate their own model solutions. The current AI product page lists options such as OpenAI, Gemini, Claude, Grok, Qwen, and Cohere; the available models and capabilities may change as the suppliers update their offerings.

Business data context

The agent can retrieve data related to the current request from the Momen database or from the configured APIs, and then add those results to the model’s context. Permissions, filtering, the number of results to be returned, and the range of fields must be controlled at the retrieval layer; reliance solely on prompt constraints is not sufficient.

Tool invocation

An Agent can use Actionflow, external APIs, and other Agents as tools, and decide whether to invoke them based on the descriptions provided for those tools. When it comes to placing orders, sending messages, reducing inventory levels, or modifying data, it is necessary to verify permissions, parameters, and the concept of idempotency within the underlying processes.

Structured output

In addition to plain text, users can define JSON structures with specific types, allowing the results to be written directly into a database, used to trigger conditional logic, or to update the user interface. The selected model must have the capability to generate the desired output, and field names, required fields, as well as format requirements must all be specified in the configuration.

Multiple rounds of dialogue and stream-based output

The platform allows for starting, continuing, stopping, and deleting conversations; it also stores the conversations, messages, content, and records of tool calls in system tables. Streamed text is suitable for real-time display on pages, but older documents indicate that such streamed content cannot be incorporated directly into subsequent data streams, and it should be verified using the current editor before deployment.

Multimodal processing

The content of Agent messages can include text, images, videos, PDFs, audio, JSON, and reasoning results, depending on the model selected. Uploading new files in a context is no longer supported; existing file contexts can still be used. For new projects, the content can be pre-processed and stored in a database or integrated with third-party RAG services.

How to create an AI Agent

1. First, define the single business task that the application is meant to address, as well as the range of data that can be read and modified.
2. Create capabilities in the Agent area, and select models that meet the requirements for text, images, videos, tools, or structured output.
3. Define the input parameters, and clearly specify the role, objectives, business rules, prohibited actions, and desired outcomes in the system prompts.
4. Configure the database or API context to limit the fields for retrieval, the filtering criteria, and the number of results returned.
5. Add Actionflow, API, or other Agent tools, and explain the purpose, parameters, and side effects of each tool.
6. Select text, structured data, or media output, and use real boundary samples in the debugging panel for testing.
7. Release the Agent, and then call it from the page, Actionflow, or Runtime API.
8. Check message logs, Token usage records, and tool usage data to continuously correct incorrect calls, manage costs, and handle failures.

AI agent workflow

1. Pages, backend processes, or external systems submit user input and business parameters.
2. The agent retrieves the relevant context from the database or API based on permissions and filtering rules.
3. The model plans the next steps based on prompts, context, and tool instructions.
4. When action is required, the model invokes published Actionflows, APIs, or other Agents.
5. The underlying processes verify identity, inputs, business rules, and the risks associated with repeated executions.
6. The model generates text, JSON, or media output, which is then written to the conversation history.
7. The frontend displays streaming content or structured fields, while the backend continues to execute deterministic processes.
8. The system logs tool requests, responses, and Token usage for troubleshooting and cost analysis.

Not all business decisions should be left to models that choose tools autonomously. Payment verification, permission checks, and status changes that must be carried out should be defined within deterministic Actionflows, in order to prevent the process from being skipped due to unexpected changes.

Build a complete web application

Momen’s visual editor organizes the interface using pages, components, containers, the CSS box model, and Flex layout. Components can be linked to databases, page variables, and various operations; forms, lists, conditional views, maps, and animations can all be connected to backend data.

1. Create a project and define user roles, core pages, data objects, and key business processes.
2. Create database tables, fields, and relationships, and then configure the read and write permissions for each role.
3. Build pages and responsive layouts on the canvas, and bind inputs, lists, and buttons to data.
4. Use Actionflow to implement validation, conditions, database updates, notifications, payments, or AI calls.
5. Configure registration, login, error states, empty data states, and loading feedback.
6. Test permissions, concurrency, boundary inputs, and failure rollback in the preview environment.
7. Select a payable package that can be published, and set the domain name, SEO settings, and computing resources.
8. After publication, monitor the logs, request rate, storage usage, traffic volume, number of processes, and AI score.

BaaS and custom frontends

Each Momen project generates a Runtime GraphQL API based on the data model and functional configurations; external frontends can use this API to query and modify data, invoke Actionflow, run AI Agents, and access configured third-party APIs. Authentication and permissions are still determined by the project’s rules.

This approach is suitable for rapidly developing the frontend using tools such as Lovable, Cursor, or custom code, while keeping the data, permissions, and backend logic visible. The user tokens must be stored properly on the frontend, and server keys should not be included in the browser code.

Tutorial on Integrating Runtime API

1. First, complete the configuration of the data model, role permissions, Actionflow, and Agents in Momen.
2. Confirm the names of queries, changes, subscriptions, and operations based on the GraphQL structure generated by the project.
3. Obtain a JWT for the end user and use an identity that corresponds to the user’s permissions in the request.
4. Start by verifying the field visibility range with the smallest possible query, and then test insertion, update, and deletion.
5. When invoking Actionflow or Agent, synchronization, asynchronous processing, timeout handling, and business errors are all managed simultaneously.
6. Protect tokens in the custom frontend, and avoid recording or sending them to untrusted services.
7. Before going live, test for unauthorized access, duplicate submissions, rate limiting, and retries in case of network failures.

The Runtime API are interfaces that are generated dynamically based on the configuration of each project; they are not a set of fixed endpoints that remain identical across all projects. When changes occur in the database structure or functions, the custom frontend also needs to verify the GraphQL operations and fields accordingly.

Code components and Run Code

When the capabilities of the built-in components are not sufficient, developers can create custom code components using React and TypeScript; these components can then be tested, published, and imported into the project using momen-cli. Such custom components have access to page data, the GraphQL client, information about the current user, as well as the runtime component tree.

• It is suitable for creating complex data visualizations, maps, advanced forms, animations, and packaging of third-party components.
• Local development requires experience with Node.js, npm, React, and TypeScript.
• Components can define properties, states, and events, and they are connected to Momen Editor’s data binding system.
• A structure check can be run before publishing, and the build results can be previewed locally.
• User tokens are sensitive credentials and must not be written to logs, public storage, or third-party analysis scripts.
• After the component library is updated, it is necessary to upgrade the version in the projects that use it.

Momen Plugin and MCP

In 2026, the authorities introduced the Momen plugin and MCP integration for Claude Code, Codex, Cursor, and other compatible tools. These coding assistants can read and modify data models, user interfaces, Actionflow configurations, bindings, permissions, and operation logs, with the results remaining available for inspection within the visual project interface.

The official GitHub repository provides information on the plugin market configuration, Skills, and integration instructions, and offers tools through momen-mcp. No explicit license is indicated on the repository page; therefore, it is not possible to assume that a plugin has a standard open-source license merely by examining its code.

Models, AI scores, and costs

Using the Momen hosting model, vectorization, and Agent calls consumes AI Points; the amount of points used depends on the model, inputs, outputs, and context tokens. If there are not enough points, Agent calls, data vectorization, and vector sorting may not be able to proceed as intended.

The monthly AI points included in the package are refreshed on a monthly basis; according to the old official guidelines, the points granted as a bonus were reset at the end of each month. For paid services, it is possible to use built-in models, but the costs associated with the model providers, as well as the costs for Momen services and database and process resources, still need to be calculated separately.

• Limit the search fields, the number of records, and the length of long texts, in order to avoid sending irrelevant context with each request.
• Choose models with lower costs for simple classification and summarization, reserving complex reasoning for tasks that truly require it.
• When structured output fails, do not retry indefinitely; instead, record the error and set a maximum number of attempts.
• Idempotent keys are used when a tool produces side effects, to prevent duplicate orders resulting from model or network retries.
• In the project details, view the score records for model, Token, Agent, and vector processing.
• Before going live, estimate the points, number of Actionflow executions, storage usage, and outbound traffic based on the actual concurrent users.

Prices and packages

As of August 20, 2026, the official website displays the equivalent price for annual billing by default. The Free plan costs $0, the Basic plan is $33 per project per month, and the Pro plan is $85 per project per month; the latter two plans are billed on an annual basis, with annual payment offering a maximum savings of 15%.

Free allows only previewing; it is not possible to use it to publish production Web applications. Paid plans are purchased on a project basis, and different packages can be chosen for each project. Educational users receive a 50% discount on the official website after verification.

Computing resources and additional packages

The package includes a basic database, object storage, outbound traffic, automatic Actionflow, and AI credits; additional resources can be purchased if these limits are exceeded. The following are the reference combinations shown on the current pricing page; it is necessary to confirm whether a specific package and billing cycle are required before placing an order.

After the project is upgraded, its functions and quotas take effect immediately, but server migration must be initiated manually by the user; the application may be temporarily unavailable during the migration process. For production projects, it is advisable to carry out the migration during periods of low traffic, and after the migration, verify login functionality, permissions, data requests, and key processes.

Which users are it suitable for

• Non-technical founders: Build the interface, database, business logic, and AI capabilities within a platform.
• Product team: Quickly test SaaS, marketing, booking, membership, and internal tools.
• AI application developers: Configure RAG, tool invocation, structured output, and multi-Agent collaboration.
• Front-end developer: Uses Momen as a hosted BaaS to control the user interface with custom code.
• Automation team: Uses Actionflow, triggers, and external APIs to create deterministic business processes.
• Educating and training users: Use free previews and current educational discounts for teaching or experimentation.
• Small technical teams: Extend between no-code and code through Runtime APIs, code components, and MCP.

Typical use cases

• AI customer service: Reads from the product database or external knowledge sources to answer questions and initiate ticketing processes.
• Travel planning: Combines user preferences, location APIs, structured itineraries, and saving functions.
• Content processing: involves classification, summarization, translation, tagging, review, and structured extraction.
• Booking and transactions: Managing inventory, time slots, users, orders, payments, and notifications.
• Internal operations: Implement approval processes, data dashboards, status updates, and scheduled automation.
• Multimedia applications: Enable models to analyze images, videos, or PDFs and write the results back to a database.
• AI-generated front-end and back-end: An coding assistant is used to build the front-end, while Momen handles data, permissions, and Agents.

Product advantages

• The frontend, data processing, backend processes, and AI Agents share the same project model, which reduces the need to combine multiple services together.
• Business rules can be kept in the visual Actionflow, which facilitates the review of deterministic logic outside the model.
• It supports various development approaches, including fully codeless solutions, BaaS, custom frontends, and code components.
• The Runtime GraphQL API enables the capabilities of a project to be invoked by external applications.
• Structured output can directly drive data updates and subsequent business processes.
• The free version provides a full editor along with a basic amount of AI resources, making it suitable for testing the architecture first.
• Resources, the number of processes, and AI points are displayed separately, which facilitates scaling up as the application grows.
• Official plugins and MCP enable the AI coding assistant to operate on a still-visualizable backend.

Usage restrictions and precautions

• The free version only allows for previewing content and retains the platform’s brand; a Basic or higher plan is required for official publication.
• The packages are charged on a per-item basis; for products that include multiple items, the subscription and resource costs must be estimated separately.
• Both Free and Basic plans have a peak rate of 5 RPS; public applications with high concurrent traffic may require the Pro plan or additional resources.
• There are risks associated with AI Agent calls, including model retirement, token costs, timeouts, incorrect calls, and failures in generating structured output.
• New projects no longer support direct creation of file upload contexts; database preprocessing or third-party RAG is required.
• After changes are made to Actionflow, Agents, APIs, or database structures, they must be republished and the dependencies tested again.
• Upgrading the package does not automatically migrate the servers, and improper handling may cause a temporary disruption to the production applications.
• Platform hosting and runtime are commercial services; the public plugin repository should not be considered to represent a fully open-source platform.
• Permanently deleting an account will affect the projects and data; it is necessary to export the data and transfer ownership before proceeding with the deletion.

Data, privacy, and account deletion

Momen’s privacy policy applies to direct users, end-users of the Momen application, hosted websites, as well as the market for templates and plugins; it outlines the bases for data processing such as contracts, legitimate interests, legal obligations, necessity, and consent. The official website states that the product is manufactured and hosted in the United States.

Databases can be exported in CSV or Excel format, and the associated media files can also be exported together. Exported files are retained for 7 days. Before performing the actual migration, it is necessary to export tables, related data, media files, permission rules, and descriptions of the business logic, rather than just saving page screenshots.

• Minimum read and write permissions are designed separately for administrators, collaborators, and end users.
• The same identity and field-level permission checks are applied to APIs, Agents, and Actionflow.
• Do not expose keys and user tokens in front-end code, code component logs, or public variables.
• Provide end-users with their own privacy policy, and explain the models connected to third-party services.
• Account deletion is a permanent action; when the sole owner of a project deletes the account, the project and all related data are removed.
• Unused subscription benefits and points are considered forfeited after the account is deleted, and they are usually not restored.
• Production applications should regularly export key data and conduct drills for platform failures or migration recovery processes.

Terms of Service and Refunds

The terms of service for Momen come into effect on March 5, 2025; this platform functions both as a visual programming tool and as a cloud hosting service. Users must be at least 18 years old, or at least 13 years old with the consent of their parents or guardians – individuals under 13 are not allowed to use it.

The official billing documentation regards the product as a virtual software service, and refunds are generally not provided after a purchase has been completed. When upgrading to a higher package, the unused days are taken into account in the new package; however, if the wrong product is purchased for an extended period, technical support fees may apply.

API, GitHub, and open-source status

Momen offers a formal Runtime GraphQL API, CLI for code components, official documentation, MCP servers, and AI development plugins, providing developers with a comprehensive set of tools. These tools are used to extend or manipulate business platforms; however, they do not mean that the backend of the platforms, the visual editors, or the hosting services are open-source.

The official Momen plugin repository is publicly accessible, but the repository page does not indicate the license used. The absence of a license does not imply that there is an automatic right to modify and redistribute the code; before using it, one should check the latest licensing documents on the repository or consult the maintenance team.

Basic information

Recommendation score

It receives a rating of 4.5 out of 5 points. Momen integrates visual interfaces, data, deterministic processes, and AI Agents seamlessly, and it also offers GraphQL, code components, and MCP, providing a comprehensive pathway from code-free prototypes to scalable applications.

The drawbacks include the complexity associated with billing based on individual projects and resource packages, the fact that the free version does not allow for production and deployment, as well as the challenges related to migration and reliance on suppliers that come with platform hosting. This approach is suitable for teams that are willing to trade visual backends in exchange for faster development speeds, and that are able to properly design mechanisms for managing permissions and costs.

Frequently Asked Questions

Is Momen free?

There is a permanent free plan that provides access to a full visual editor, 1 API, 1 Actionflow, 1 Agent, as well as basic resources. Projects created under this free plan can only be viewed in preview mode; they cannot be released as actual production Web applications.

How much are Basic and Pro?

The current annual payment rates are $33 and $85 per project per month, respectively. The monthly pricing, taxes, and any discounts for promotions are subject to the details on the purchase page.

Can Momen build a complete application?

Yes, the platform covers pages, databases, business processes, user permissions, AI, domain names, and hosting. For complex products, data modeling, permission testing, operation and maintenance, as well as cost control are still necessary.

Can Momen be used solely as the backend?

Yes. The Runtime GraphQL API enables custom frontends to access data, Actionflow, Agents, and third-party APIs; it is well-suited for use in combination with React, Next.js, Vue, or AI-generated interfaces.

Which AI models are supported?

The current AI product page lists models such as OpenAI, Gemini, Claude, Grok, Qwen, and Cohere; it also allows users of paid plans to incorporate their own models. The specific models, tools, and multimodal capabilities are shown in the real-time list provided by the editor.

What are AI Points?

It is the unit used to measure the consumption of Momen’s AI hosting services; model inputs, outputs, context, vectorization, and Agent calls all result in the consumption of these points. The number of tasks cannot be determined solely based on these points, as there are significant differences among different models and token lengths.

Are APIs provided?

It provides a Runtime GraphQL API; each project generates its own structure based on its data model and functions. This API allows for querying and modifying data, as well as invoking Actionflow, Agent, and other configured third-party APIs.

Can it be extended with code?

Code components can be developed using React and TypeScript, and it is also possible to extend the functionality through custom frontends, code blocks, GraphQL, CLI, plugins, and MCP. Some of these capabilities require experience with Node.js and front-end development.

Is Momen open source?

The complete platform is not an open-source project. The official plugin repository is accessible to the public, but no explicit license is indicated there; moreover, the publicly available code does not mean that the entire commercial platform is open source.

Is private deployment supported?

The standard package is hosted on Momen’s cloud platform; for information regarding private deployment, it is necessary to contact the team. Options such as BYOC, dedicated instances, data zones, and operational boundaries should be specified in the enterprise plan.

Is it possible to export data?

Database tables and views can be exported in CSV or Excel format, and related media can also be packaged. Exporting data does not mean that the visual elements of the application can be exported as well; before migration, it is necessary to assess separately the costs associated with rebuilding pages and processes.

Can I get a refund after purchasing?

The official documentation states that refunds are generally not available once a virtual software service has been purchased. The unused days from a previous subscription are taken into account when upgrading to a new plan; it is necessary to confirm the details of the service, its duration, the allocated quota, and the server requirements before making a payment.