# MCPFusion Developer Prover MCP for AI Agents AI Agent Connect

> MCPFusion Developer Prover helps you build Connectors that actually follow the MCPFusion framework. It stops your AI client from taking shortcuts like using raw Zod schemas or skipping Presenters. By forcing structured reflection, it ensures your architecture stays clean and your tools behave exactly how the framework intended.

## Overview
- **Category:** productivity
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_kq18iP2KBas7gK6lLEfjXD7wkf1LFvR2zOIJQ4BQ/ai-agent-connect
- **Tags:** mcpfusion, mva-architecture, mcp-server, structured-reasoning, decision-pivots, definemodel, presenter, agentic-pipeline

## Description

You're building an Connector, and your AI client keeps trying to cut corners. It wants to dump raw Zod objects into your tool files and skip the Presenter layer entirely because that's what it saw in its training data. The problem is that while the code might run, it violates every principle of the MCPFusion framework, leaving you with a mess of hidden fields, inconsistent verbs, and logic that's hard to maintain. This Connector fixes that by acting as a gatekeeper. It forces your agent to prove it understands the Model-View-Agent architecture before it's allowed to commit code. It checks if you're actually using defineModel for your entities, ensures your tools have the right Presenter attached for egress validation, and makes sure you aren't using mutation verbs for read-only queries. Instead of just guessing if the code is good enough, you get a structured verdict on whether the implementation is architecturally sound. It's like having a senior architect review every line of code to make sure it fits the blueprint. You can find this tool in the Vinkius catalog to keep your framework-specific code from drifting into technical debt.

## Tools

### validate_mcpfusion_implementation
Check if your code follows the MVA pattern and provides a detailed verdict on schema, verbs, and layering.

## Prompt Examples

**Prompt:** 
```
I'm making a tool to fetch user profiles. Here is my code: [code]. Is this right for MCPFusion?
```

**Response:** 
```
Verdict: RAW_SCHEMA_DETECTED. Use defineModel('User', m => { m.casts({ name: m.string(), email: m.string() }) }) in models/. Create UserPresenter in views/. Tool uses .returns(UserPresenter). Handler returns raw data; Presenter handles the rest.
```

**Prompt:** 
```
I'm using f.mutation to let the AI search the logs. Does that follow the rules?
```

**Response:** 
```
Verdict: SEMANTIC_VERB_WRONG. Search is a READ; use f.query('logs.search') instead of f.mutation(). mutation is for destructive actions like create or delete. Also, .handle() auto-wraps with success() so you should remove the manual success() call and just return the data.
```

**Prompt:** 
```
Can you check if I've separated my models and views correctly in this file?
```

**Response:** 
```
Verdict: MVA_VIOLATED. Model and Agent logic are mixed in one file. MVA enforces conceptual separation: Models define data shapes, Presenters handle egress, and Tools expose to LLMs. Move the .handle() logic to the proper agent layer.
```

## Capabilities

### Verify MVA architecture compliance
Checks if your code follows the Model-View-Agent pattern instead of mixing logic.

### Detect raw Zod schema violations
Identifies where the agent used raw Zod instead of the required defineModel function.

### Check for missing Presenters
Ensures every data-returning tool has a Presenter for egress validation.

### Validate semantic verb usage
Verifies that f.query and f.mutation are used correctly for reads and writes.

### Audit file structure separation
Confirms that models, views, and agents stay in their own dedicated modules.

### Enforce auto-wrapping logic
Checks that you aren't manually calling success() when .handle() does it automatically.

## Use Cases

### The Shortcut Taker
A developer writes a tool and the AI uses z.object() to save time. The prover catches this and forces the use of defineModel.

### The Verb Mixer
An agent uses f.mutation for a simple search query. The prover flags the semantic error and tells the dev to use f.query instead.

### The Data Leak
A tool returns a user object with a password hash. The prover identifies the missing Presenter and tells the dev to add one.

### The Spaghetti Code
Logic is mixed in the tool file instead of the models layer. The prover demands a move to the correct directory.

## Benefits

- Stop your AI client from using raw Zod schemas that leak sensitive data by enforcing defineModel via validate_mcpfusion_implementation.
- Prevent raw JSON leaks by ensuring every data-returning tool has a Presenter attached to handle egress validation and rules.
- Keep your agent behavior predictable by enforcing correct semantic verbs like f.query and f.mutation for clear side-effect mapping.
- Eliminate manual success() wrapping errors because the tool checks for .handle() auto-wrapping to keep your handlers clean.
- Maintain a clean codebase by auditing the separation of models, views, and agents to prevent logic from leaking into the wrong layer.
- Get instant feedback on MVA violations with structured reflection rather than guessing if your code meets the framework's core requirements.

## How It Works

The bottom line is you get an architectural gatekeeper that prevents your AI from writing non-compliant framework code.

1. Provide the AI client with the specific MCPFusion code or tool definition you just wrote.
2. Invoke the validation tool to run a structured reflection check on that code.
3. Review the generated verdict and apply the specific architectural fixes suggested by the tool.

## Frequently Asked Questions

**What is the MCPFusion Developer Prover?**
It's a validation tool that ensures your Connector development follows the Model-View-Agent (MVA) architecture. It checks your code for framework compliance.

**How does it help with MVA architecture?**
It forces your AI client to follow specific layering rules, ensuring that data models, UI presenters, and tool logic stay separated and consistent.

**Can it catch security leaks like hidden fields?**
Yes. By enforcing the use of defineModel() instead of raw Zod schemas, it ensures that sensitive fields like password hashes aren't accidentally exposed.

**Does it work with any AI client?**
Yes, it works with any MCP-compatible client like Claude, Cursor, or Windsurf to help guide your development process.

**How does it handle semantic verbs?**
It checks that you use the correct verbs for the right actions, like f.query for reads and f.mutation for writes, which helps your agent understand side effects.

**Why should I use this instead of a standard linter?**
While a linter checks syntax, this tool performs structured reflection on your architectural choices, specifically tailored for the MCPFusion framework.

**Does this generate Connector code?**
No. The agent writes the code. This tool VALIDATES that the code follows MCPFusion's MVA architecture — defineModel() for entities, Presenters for egress, semantic verbs for operations, and correct file structure. It teaches the framework through rejection messages.

**Why does the LLM need this if it can read documentation?**
Documentation reading is one-shot — the LLM reads once and forgets. This tool forces structured reflection on EVERY tool being built. Each field is a micro-lesson: modelStrategy forces naming m.casts() fields, presenterStrategy forces explaining .returns(), toolDesign forces choosing the right semantic verb. Repetition through obligation, not suggestion.

**What if my Connector doesn't return data (reasoning-only)?**
Reasoning Connectors still use MVA. The Model defines the verdict/message shape. The Presenter renders the verdict. The tool forces structured input. Even a tool that computes nothing needs defineModel() for its response and a Presenter for its output. The same architecture applies — the Presenter is the egress contract.

**Does this generate MCP server code?**
No. The agent writes the code. This tool VALIDATES that the code follows MCPFusion's MVA architecture — defineModel() for entities, Presenters for egress, semantic verbs for operations, and correct file structure. It teaches the framework through rejection messages.

**What if my MCP doesn't return data (reasoning-only)?**
Reasoning MCPs still use MVA. The Model defines the verdict/message shape. The Presenter renders the verdict. The tool forces structured input. Even a tool that computes nothing needs defineModel() for its response and a Presenter for its output. The same architecture applies — the Presenter is the egress contract.