---
title: "RevCent MCP Interface"
description: "A non-technical overview of the RevCent MCP as the AI-native interface for asking business questions, creating and configuring RevCent resources, running authorized operations, monitoring account activity, producing reporting insights, discovering improvements, and giving AI IDEs, AI chats, and AI agents an alternative to the Web App and API."
type: "interface"
company: "RevCent"
canonical: "https://revcent.com/documentation/markdown/ecosystem/interface/MCP.md"
technical_links:
  setup: "https://kb.revcent.com/tools/ai/mcp"
  mcp_markdown_index: "https://revcent.com/documentation/markdown/mcp/index.md"
  mcp_guide_index: "https://revcent.com/documentation/markdown/mcp/guide/index.md"
  mcp_operation_index: "https://revcent.com/documentation/markdown/mcp/operation/index.md"
  server_endpoint: "https://mcp.revcent.com"
  setup_instructions: "https://kb.revcent.com/en/tools/ai/mcp#instructions"
---

# RevCent MCP Interface

The RevCent MCP is the AI and AI-agent interface for the RevCent ecosystem.

MCP stands for Model Context Protocol. In practical RevCent terms, the RevCent MCP lets AI clients, AI assistants, AI agents, automation systems, IDE agents, reporting agents, and operational copilots connect directly to a RevCent account through structured tools.

The Web App is the human interface. The API is the software developer interface. The MCP is the AI interface.

The MCP was created to give users the option to let their AI IDE, AI chat, AI assistant, or AI agent do many of the same RevCent tasks they could otherwise do through the Web App or the API. Instead of forcing every action into a manual click path or a developer-built integration, the MCP gives AI a governed way to ask questions, retrieve context, create resources, configure settings, run authorized operations, and help manage the business from a conversational or agentic environment.

In that sense, the MCP is not only a companion to the Web App and API. It is an alternative interface for users who want AI to help operate RevCent directly.

That distinction matters because modern businesses increasingly want to ask questions, get answers, monitor operations, find problems, and improve performance through AI. The RevCent MCP gives AI a governed path into the business context stored in RevCent, including customers, sales, subscriptions, payments, products, shops, refunds, disputes, fraud signals, reporting, projects, notes, AI Assistants, AI Voice Agents, Functions, and other ecosystem entities.

## Core Purpose

The purpose of the RevCent MCP is to let users and AI agents interact with RevCent through natural language and intelligent workflows.

Instead of requiring every business question to become a manual dashboard search, spreadsheet export, support request, or custom API integration, the MCP allows an AI client to ask RevCent for context, retrieve relevant account information, run reporting workflows, explain what is happening, and help decide what should happen next.

The MCP also allows AI to do work, not only describe work. With the right permissions and user intent, AI can create, configure, update, organize, trigger, and run RevCent operations that would otherwise be performed manually in the Web App or programmatically through the API. That can include setup assistance, configuration review, resource creation, operational workflows, reporting workflows, project documentation, and guided business actions.

For a user, that means the MCP can turn questions such as “what happened today?” or “why are renewals down?” into direct analysis against RevCent account data.

For an AI agent, that means the MCP can become a controlled business interface for monitoring, insight generation, reporting, and workflow assistance.

## MCP as an Alternative Interface

The RevCent MCP is intended as an alternative way to interact with RevCent alongside the Web App and API.

A user can still use the Web App to click through RevCent manually. A developer can still use the API to build direct software integrations. The MCP adds a third path: AI can use RevCent tools on the user's behalf.

This matters because many users do not want to choose between manual work and custom development. They want to ask an AI system to help them understand, configure, monitor, improve, and operate their business.

Through MCP, an authorized AI client can help with actions such as:

| AI-Assisted Action | What It Means |
|---|---|
| Ask questions | The user can ask plain-English questions about sales, customers, subscriptions, renewals, refunds, products, shops, projects, and account activity. |
| Retrieve context | AI can look up the relevant RevCent records and connect related entities before answering. |
| Create resources | AI can help create supported RevCent resources when the user wants something new configured or documented. |
| Configure resources | AI can help adjust supported settings, profiles, templates, agents, projects, notes, or other resources when permitted. |
| Run operations | AI can trigger authorized RevCent operations through MCP instead of requiring the user to manually perform the same action in the Web App or write API code. |
| Monitor activity | AI agents can check for meaningful business changes, exceptions, risks, and opportunities. |
| Produce reporting | AI can turn RevCent activity into business summaries, trends, comparisons, and explanations. |
| Recommend improvements | AI can identify optimizations across revenue, recovery, products, subscriptions, shops, campaigns, support, and operations. |

The MCP should therefore be understood as the AI-operable surface of RevCent. It gives users the option to let AI interact with the ecosystem in a controlled way, while still respecting permissions and the seriousness of account-changing operations.


## MCP Documentation Index

The complete MCP documentation is available through the RevCent MCP Markdown index:

[RevCent MCP Markdown Index](https://revcent.com/documentation/markdown/mcp/index.md)

That index contains both MCP guides and the complete MCP operation reference. It is the best starting point for AI systems, developers, and automation builders that need to understand what the RevCent MCP can do and how the MCP fits into the broader RevCent ecosystem.


## Technical Links

| Area | Link |
|---|---|
| MCP Setup | `https://kb.revcent.com/tools/ai/mcp` |
| MCP Markdown Index | `https://revcent.com/documentation/markdown/mcp/index.md` |
| MCP Guide Index | `https://revcent.com/documentation/markdown/mcp/guide/index.md` |
| MCP Operation Index | `https://revcent.com/documentation/markdown/mcp/operation/index.md` |
| MCP Server Endpoint | `https://mcp.revcent.com` |
| OAuth Client Permissions | `https://kb.revcent.com/en/integrations/revcent-oauth#permissions` |
| OAuth Clients | `https://revcent.com/user/oauth-clients` |
| MCP Setup Instructions | `https://kb.revcent.com/en/tools/ai/mcp#instructions` |
| API Interface Markdown | `https://revcent.com/documentation/markdown/ecosystem/interface/API.md` |
| Web App Interface Markdown | `https://revcent.com/documentation/markdown/ecosystem/interface/WebApp.md` |

## Why the MCP Is Important

The MCP is important because it lets RevCent become AI-operable.

A traditional system waits for a human to click through pages or for a developer to build a custom integration. An MCP-connected RevCent account can be accessed by AI tools that understand the user’s question, retrieve the right context, analyze the result, and help the user act.

This creates a practical bridge between business intent and operational execution.

A user can ask about sales, customers, subscriptions, renewals, refunds, disputes, product performance, campaign performance, shop health, payment outcomes, failed payments, support issues, and reporting trends without first knowing exactly where every record lives.

The same user can also ask AI to help perform supported work: create a Project, save a Project Note, configure an AI workflow, prepare an Email Template, create a customer-facing resource, review settings, trigger a permitted operation, or guide a business process that would otherwise require Web App clicks or API calls.

An AI agent can monitor for changes, generate insights, surface problems, recommend next steps, run approved workflows, and help improve the business over time.

## The MCP as a Business Conversation Layer

The RevCent MCP lets users connect AI directly to their RevCent account and ask business questions conversationally.

Examples of questions a user could ask through an MCP-connected AI client include:

| Business Question | What MCP Makes Possible |
|---|---|
| “How much revenue did we make today?” | The AI can use RevCent reporting context to analyze current revenue activity. |
| “Which products are performing best this week?” | The AI can compare product-related sales and identify top performers. |
| “Why are subscriptions overdue?” | The AI can inspect subscription and renewal context and explain likely causes. |
| “Which renewals failed recently?” | The AI can identify failed renewal activity and organize it into an actionable review. |
| “Are refunds increasing?” | The AI can compare refund patterns and summarize what changed. |
| “Which customers need follow-up?” | The AI can surface customers connected to payment failures, disputes, renewals, or support context. |
| “What should I look at before launching this offer?” | The AI can review related Products, Campaigns, Shops, Payment Profiles, Shipping Profiles, and prior Project Notes. |
| “What changed since yesterday?” | The AI can compare recent account activity and summarize meaningful changes. |

The value is not only retrieval. The value is interpretation. MCP-connected AI can help turn RevCent activity into plain-English business understanding.

## MCP for AI Agents

The MCP is especially powerful for AI agents because agents can work continuously or on a schedule around specific business goals.

An AI agent connected through MCP can act like a specialized business analyst, operations assistant, monitoring system, reporting assistant, or growth optimization assistant.

Examples of MCP-powered agents include:

| Agent Type | Business Value |
|---|---|
| Reporting Agent | Produces recurring summaries of revenue, subscriptions, products, shops, campaigns, refunds, and customer activity. |
| Monitoring Agent | Watches for failed renewals, disputes, chargebacks, fraud detections, shop issues, refund spikes, and other meaningful changes. |
| Revenue Recovery Agent | Identifies recoverable failed payments, salvage opportunities, overdue subscriptions, and follow-up needs. |
| Subscription Agent | Reviews subscription health, renewal performance, overdue activity, churn signals, and customer lifecycle patterns. |
| Product Performance Agent | Looks for product-level trends, underperforming offers, refund-heavy products, or strong candidates for promotion. |
| Shop Health Agent | Helps monitor connected shops, WooCommerce activity, validation issues, and storefront-to-RevCent flow health. |
| Customer Support Agent | Retrieves customer, sale, subscription, refund, shipment, and payment context before recommending support actions. |
| Optimization Agent | Looks for patterns that suggest configuration, pricing, product, campaign, recovery, or operational improvements. |

This is why the MCP should be understood as more than a technical connector. It is the foundation for AI-assisted business operations inside RevCent.

## Monitoring and Alerts

The MCP can support monitoring workflows where AI checks RevCent activity and highlights what matters.

Monitoring can focus on questions such as:

- Are failed subscription renewals increasing?
- Are refunds higher than normal?
- Are chargebacks or PayPal disputes appearing?
- Are specific products producing more support risk?
- Are campaigns generating lower-quality customers?
- Are certain shops having configuration or payment issues?
- Are salvage opportunities being missed?
- Are AI Assistants or AI Voice Agents creating useful outcomes?
- Are customer portal interactions reducing support load?
- Are payment, shipping, tax, or fulfillment patterns changing?

The MCP is valuable because monitoring can be connected to business context. Instead of only reporting that something happened, an AI agent can help explain why it might matter and what the user may want to review next.

## Reporting and Insight

The MCP can help AI produce reporting and insight directly from RevCent context.

A user can ask for business summaries, comparisons, trends, and anomalies in natural language. An AI agent can then gather the relevant RevCent context and turn it into a useful explanation.

Useful reporting themes include:

- revenue by day, week, month, campaign, shop, or product,
- subscription renewal performance,
- failed payment patterns,
- refund and chargeback trends,
- customer growth and repeat purchase behavior,
- product performance and product-group performance,
- campaign quality and acquisition performance,
- shop performance,
- subscription churn signals,
- trial conversion behavior,
- payment recovery opportunities,
- operational exceptions that need human attention.

The strongest value is the combination of reporting plus explanation. The MCP helps AI answer not only “what happened?” but also “what does it mean?” and “what should we look at next?”

## Optimization and Business Improvement

The MCP can help AI agents find optimizations that a business may otherwise miss.

Examples include:

| Optimization Area | Possible MCP-Driven Insight |
|---|---|
| Payment Recovery | Identify failed payments that appear recoverable and deserve follow-up. |
| Subscription Retention | Detect overdue subscriptions, churn signals, or renewal friction. |
| Product Strategy | Find products with strong revenue, weak conversion, high refunds, or high support burden. |
| Campaign Quality | Compare campaigns by revenue quality, refund rate, customer value, and subscription behavior. |
| Shop Performance | Identify storefronts that produce strong sales or repeated operational issues. |
| Support Efficiency | Surface customers or sales that need attention before they become escalations. |
| Fulfillment Review | Highlight shipping or fulfillment patterns that may affect customer experience. |
| AI Workflow Improvement | Review how AI Assistants, AI Voice Agents, Functions, and Email Templates are contributing to operations. |

This makes the MCP useful for more than answering questions. It can become a continuous improvement layer for the business.

## Direct User Interaction Examples

A user connected to RevCent through an MCP-enabled AI client could ask:

- “Show me the most important things that happened in my RevCent account today.”
- “Summarize yesterday’s sales and tell me what looks unusual.”
- “Which products are generating the most revenue but also the most refunds?”
- “Which subscriptions are overdue and worth follow-up?”
- “Find failed renewals that look recoverable.”
- “What customers should support look at first?”
- “Compare this week’s subscription renewals to last week.”
- “Which campaigns are producing the best customers?”
- “What should I improve in my checkout or payment setup?”
- “Create a project note summarizing what changed and what I should review.”
- “Create a new project for this launch and connect the relevant context.”
- “Configure this workflow based on the product and subscription setup we discussed.”
- “Run the appropriate operation to check whether this shop is configured correctly.”
- “Create the resource we need, but explain what you are going to do before you do it.”

These examples show why MCP is powerful: the user does not need to start from a specific page, report, export, or endpoint. The user can start with a business question.

## AI Agent Workflow Examples

MCP-connected agents can also be designed around repeatable workflows.

A reporting workflow could:

1. Review recent sales, refunds, subscriptions, renewals, and product performance.
2. Summarize important changes.
3. Highlight anomalies or opportunities.
4. Save the result to a Project Note.
5. Notify the user or another system when attention is needed.

A configuration workflow could:

1. Understand the user's business goal.
2. Review the relevant RevCent context and documentation.
3. Identify what must be created or configured.
4. Explain the planned changes.
5. Create, edit, trigger, or organize the approved RevCent resources through authorized MCP operations.
6. Save a Project Note documenting what changed and why.

A monitoring workflow could:

1. Check for failed renewals, disputes, chargebacks, fraud detections, or shop issues.
2. Decide whether the issue is meaningful.
3. Gather related customer, sale, subscription, product, and payment context.
4. Recommend a next step.
5. Escalate only when the issue deserves attention.

An optimization workflow could:

1. Review patterns across products, campaigns, customers, subscriptions, and refunds.
2. Identify likely opportunities.
3. Compare the opportunity against historical context.
4. Suggest improvements.
5. Create a Project Note so the recommendation becomes durable business memory.

## MCP and Projects

Projects and Project Notes are especially useful with the MCP because they give AI a durable place to store context, decisions, findings, and business memory.

A Project can act as a workspace for a launch, migration, reporting review, optimization effort, recovery initiative, campaign analysis, or AI-agent workflow.

Project Notes help preserve the “why” behind a decision. That is especially important for AI agents, because future sessions can review prior notes before making new recommendations.

A strong MCP pattern is:

| Step | Purpose |
|---|---|
| Find the relevant Project | Establish the business context. |
| Read recent Project Notes | Understand prior decisions and warnings. |
| Retrieve related RevCent context | Ground the analysis in actual account relationships. |
| Analyze or act | Answer the user’s question or perform the authorized workflow. |
| Create a new Project Note | Preserve the result for future users and agents. |

## MCP and Permissions

The MCP is powerful, so permissions matter.

RevCent recommends creating OAuth clients for specific MCP use cases and limiting permissions based on the purpose of each AI client or agent. For example, a reporting agent should not need the same permissions as an agent that can edit configuration or trigger operational workflows.

Common patterns include:

| MCP Client Type | Permission Strategy |
|---|---|
| Personal AI client | Allow only the actions the user actually wants to perform through AI. |
| Reporting agent | Focus on reporting and read-oriented permissions. |
| Monitoring agent | Focus on retrieval, reporting, and alerting context. |
| Support assistant | Allow access to customer, sale, subscription, refund, shipping, and payment context as needed. |
| Operational agent | Grant only the specific action permissions required for that workflow. |

The principle is simple: give each MCP client enough access to do its job, but not more than it needs.

## MCP Compared to the Web App

The Web App is best for human review, setup, configuration, and manual operations.

The MCP is best for AI-assisted questions, reporting, monitoring, agent workflows, context-aware automation, and AI-guided operation of RevCent.

Many tasks that a user could perform manually in the Web App can also be assisted through MCP when the AI client has the correct permissions and the user wants AI to help. The difference is the interaction model: the Web App is click-driven, while the MCP is conversation-driven and agent-driven.

Most businesses benefit from using both:

| Interface | Best Use |
|---|---|
| Web App | Human users configure, inspect, and manually manage RevCent. |
| MCP | AI users and AI agents ask questions, retrieve context, create and configure supported resources, run authorized operations, monitor activity, produce reports, and recommend improvements. |

The Web App gives humans direct visual control. The MCP gives AI a structured path to help users do comparable work through chat, IDEs, copilots, and agents.

## MCP Compared to the API

The API is designed for developers and software systems. It is the right interface when building a traditional integration, backend service, checkout flow, or application-to-application connection.

The MCP is designed for AI and AI agents. It is the right interface when the user wants an AI system to understand RevCent context, choose relevant tools, answer questions, run analysis, monitor activity, assist with operations, and perform authorized actions without requiring the user to write API code.

Many capabilities exposed through the API can also be made available to AI through the MCP. The difference is that the API expects a developer or software system to know which endpoint to call, while the MCP lets an AI client reason through the user's goal, retrieve context, consult documentation, select the appropriate operation, and explain the result.

| Interface | Primary Audience | Best For |
|---|---|---|
| API | Developers and software systems | Custom software integrations and direct endpoint-based workflows. |
| MCP | AI systems and AI agents | Natural-language business questions, AI-assisted creation and configuration, authorized operation execution, reporting, monitoring, insight, automation, and optimization. |

The API connects software to RevCent. The MCP connects AI to RevCent and gives users an AI-native alternative to direct API work.

## Ecosystem Benefits

The RevCent MCP benefits the ecosystem because it turns RevCent data and operations into an AI-accessible business layer.

Key benefits include:

- users can ask business questions without knowing exactly where to look,
- users can ask AI to create, configure, organize, trigger, and run supported RevCent operations when permitted,
- AI IDEs, AI chats, and AI agents can become practical alternatives to manual Web App work or direct API development,
- AI agents can monitor account activity and detect meaningful changes,
- reporting can become conversational and recurring,
- operational issues can be surfaced earlier,
- revenue recovery opportunities can be identified more consistently,
- Project Notes can preserve business memory across sessions,
- AI can help connect relationships across customers, sales, products, subscriptions, shops, payments, refunds, disputes, and fulfillment,
- teams can use AI as a business copilot instead of only a chat interface,
- external agents can use RevCent as an operational source of truth.

## Summary

The RevCent MCP is the AI-native interface for the RevCent ecosystem.

It allows users to connect AI directly to their RevCent account, ask practical business questions, generate reporting insights, create and configure supported resources, run authorized operations, monitor operational activity, preserve findings, and discover ways to improve the business.

The complete list of MCP operations and guides is maintained in the RevCent MCP Markdown index:

[RevCent MCP Markdown Index](https://revcent.com/documentation/markdown/mcp/index.md)

For businesses that want AI agents to help with monitoring, insight, reporting, revenue recovery, customer support, optimization, and automation, the MCP is the most important interface into RevCent.

## How to Create an OAuth Client and Connect to the MCP

To use the RevCent MCP, an AI client, AI IDE, AI chat, copilot, or AI agent needs authorized access to the user's RevCent account. RevCent supports this through OAuth Clients.

An OAuth Client should be created for the specific AI use case that will connect to the MCP. For example, a user may create one OAuth Client for a personal AI chat, another for a reporting agent, and another for a monitoring agent. This makes access easier to understand, easier to audit, and safer to limit by permission.

### MCP Server Endpoint

The RevCent MCP server endpoint is:

`https://mcp.revcent.com`

This is the server URL an AI tool should use when adding RevCent as a custom MCP server.

### Step-by-Step Connection Instructions

| Step | What To Do | Why It Matters |
|---|---|---|
| 1 | Log in to RevCent and go to `https://revcent.com/user/oauth-clients`. | OAuth Clients are created inside the authenticated RevCent account. |
| 2 | Click the **Create New OAuth Client** button. | This creates a dedicated connection record for the AI client, chat, IDE, or agent. |
| 3 | Give the OAuth Client a name based on the AI use case. | Clear names help users understand which AI system has access, such as “Personal AI Chat,” “Reporting Agent,” or “Monitoring Agent.” |
| 4 | After creating the OAuth Client, open the new client's edit page. | The edit page is where the connection details and permissions can be reviewed. |
| 5 | Open the **Auth Details** tab. | This tab contains the credentials the AI tool needs to connect. |
| 6 | Copy the **Client ID** and **Client Secret**. | These credentials identify the OAuth Client when the AI tool connects to RevCent MCP. |
| 7 | In the AI tool, add a custom MCP server using `https://mcp.revcent.com`. | This points the AI client or agent to the RevCent MCP server. |
| 8 | Enter the Client ID and Client Secret when the AI tool asks for OAuth credentials. | This lets the AI tool begin the RevCent authorization process. |
| 9 | Complete the authorization flow. | Once authorized, the AI tool can access the RevCent account through the permissions granted to that OAuth Client. |
| 10 | If the AI tool only accepts an access token, manually create an OAuth access token for that client. | This gives users a fallback connection option for AI tools that do not support the full OAuth client setup flow. |
| 11 | Review and limit permissions before using the MCP. | The MCP can perform powerful account operations, so each AI client should only have the access it needs. |

### Recommended OAuth Client Patterns

| MCP Use Case | Recommended OAuth Client Pattern |
|---|---|
| Personal AI chat | Create one OAuth Client for the user's personal AI interaction with RevCent. |
| AI IDE or coding assistant | Create an OAuth Client scoped to the RevCent work the IDE agent is expected to perform. |
| Reporting agent | Create an OAuth Client focused on reporting, read access, and BigQuery/reporting-related operations. |
| Monitoring agent | Create an OAuth Client focused on retrieval, reporting, alerting, and issue detection. |
| Operational agent | Create an OAuth Client with only the specific create, edit, trigger, or action permissions needed for that workflow. |
| Support assistant | Create an OAuth Client limited to the customer, sale, subscription, refund, shipping, and payment context required for support work. |

### Permissions Before Connection

The RevCent MCP can give AI access to many account operations. Some operations can create resources, edit configuration, trigger workflows, process actions, or otherwise change the RevCent account.

Because of that, RevCent recommends using the principle of least privilege:

- create a separate OAuth Client for each AI client or agent,
- enable only the permissions that AI client needs,
- avoid giving reporting or monitoring agents refund, edit, delete, or other consequential permissions,
- give operational agents only the specific action permissions required for their job,
- review OAuth Client permissions before authorizing an AI tool,
- adjust permissions as the AI use case changes.

This permission model is what makes the MCP practical as an alternative to the Web App and API. A user can let AI operate RevCent directly, but still control which operations the AI is allowed to use.

### Why the OAuth Setup Matters

The OAuth Client is the bridge between a user's RevCent account and an AI system.

Without OAuth, the AI tool has no governed way to access RevCent. With a properly scoped OAuth Client, the user can decide which AI chat, IDE, copilot, or agent is allowed to connect, what it is allowed to retrieve, and what actions it is allowed to perform.

That makes the MCP useful for both simple conversational access and more advanced agent workflows. A user can start by asking questions, then expand into reporting, monitoring, project documentation, optimization workflows, setup assistance, and authorized account operations as trust and permissions increase.



---
Document Parent Directory
* [Interfaces](https://revcent.com/documentation/markdown/ecosystem/interface/index.md) - Non-technical markdown documentation for ways to interact and connect with the RevCent ecosystem, including the MCP, API, and Web App.