How to Use the Accessibility Prover MCP in LlamaIndex

Q: Can I filter which MCP tools LlamaIndex agents can access?

Yes, you can use the allowedtools filter during agent setup. This restricts your agent to only calling the accessibility check when evaluating frontend code.

Index WCAG compliance results and ground your LlamaIndex RAG applications in accessible UI patterns.

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Connect Accessibility Prover MCP to LlamaIndex

Create your Vinkius account to connect Accessibility Prover to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Accessibility Prover with LlamaIndex

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Index compliance data using this MCP Server

Evaluating UI views and writing the compliance results directly into your index is handled by the `validate_accessibility` tool. LlamaIndex stores these validated structures, creating a searchable knowledge base of accessible components. Future design queries pull from this verified index instead of generating components from scratch. This prevents your RAG pipeline from repeating past accessibility mistakes in new code.

Ground UI generation in verified WCAG standards

Checking components for keyboard tab order, ARIA annotations, and motion media queries is what the `validate_accessibility` tool does before indexing. Your agent queries this historical data to find pre-approved layouts that already pass EAA 2025 rules. This approach eliminates hallucinations by grounding the agent in concrete, verified design structures. You stop relying on generic LLM knowledge and start using a factual database of compliant UI code.

Enforce strict contrast checks on retrieved nodes

To ensure they meet the 4.5:1 contrast ratio threshold, the `validate_accessibility` tool processes retrieved code nodes. If a retrieved node fails this check, your agent rejects it and searches for a compliant alternative. This guardrail maintains the integrity of your vector database. Only components with explicit form-label relationships and proper focus indicators make it into your production-ready index.

Setup guide

Set up Accessibility Prover MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Accessibility Prover MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Accessibility Prover tools.",
)
response = await agent.run("List recent Accessibility Prover data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Accessibility Prover. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Accessibility Prover MCP in LlamaIndex

You initialize the client with llama-index-tools-mcp and convert it using McpToolSpec. This exposes the validate_accessibility tool directly to your LlamaIndex agents.

Yes, because tool outputs are indexed into your vector store. Your system can run semantic searches over previous validation runs to find compliant design patterns.

No, the server analyzes raw HTML structures, CSS properties, and ARIA attributes statically. This makes it fast enough to run inside real-time query pipelines.

Yes, you can use the allowed_tools filter during agent setup. This restricts your agent to only calling the accessibility check when evaluating frontend code.

Your CSS styling rules, ARIA attributes, and DOM structures are evaluated inside an isolated, zero-trust runtime environment. Vinkius secures the session token and destroys the container immediately after validation, preventing data leaks.

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