How to Use the AccuLynx MCP in LlamaIndex

Q: Can I index AccuLynx lead lists into a vector store using LlamaIndex?

Yes, you can run listleads to retrieve recent roofing prospects and load them into a VectorStoreIndex. This lets you perform semantic searches over all your active roofing inquiries.

Search and index your AccuLynx roofing leads and job financials directly within LlamaIndex RAG pipelines using this MCP Server.

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Connect AccuLynx MCP to LlamaIndex

Create your Vinkius account to connect AccuLynx 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 AccuLynx with LlamaIndex

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Index roofing leads into LlamaIndex

This integration uses the `list_leads` tool to pull active roofing prospects and feed them straight into your vector database. LlamaIndex stores these records as document nodes, making your historical lead data instantly searchable. Your query engine can then parse past inquiries to find patterns in roofing project requests. You get answers grounded in real lead history without querying the live database repeatedly.

LlamaIndex RAG for roofing job metadata

This setup runs the `get_job_details` tool to extract milestones and structural specifications for specific roofing jobs using our secure MCP connection. The tool output is parsed and cached directly into your local index for semantic retrieval. When users ask about project status, LlamaIndex pulls the latest cached milestones instead of guessing. This keeps your customer support responses accurate and grounded in actual job records.

Query roofing payments with this MCP Server

This tool configuration uses `list_payments` to fetch financial transactions and payment histories for a designated job. LlamaIndex indexes these financial nodes so your agent can cross-reference paid balances during customer queries. By keeping this data in your query index, you can run complex financial audits using simple natural language. The system matches payment histories against job records without manual spreadsheet lookups.

Setup guide

Set up AccuLynx 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 AccuLynx 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 AccuLynx tools.",
)
response = await agent.run("List recent AccuLynx 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 AccuLynx. 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 AccuLynx MCP in LlamaIndex

Install the llama index MCP adapter and instantiate the BasicMCPClient pointing to your server URL. Use `McpToolSpec` to convert the tools and pass them directly to your FunctionAgent.

Yes, you can run `list_leads` to retrieve recent roofing prospects and load them into a VectorStoreIndex. This lets you perform semantic searches over all your active roofing inquiries.

The framework reads the tool schema and forces your agent to collect the first and last name before execution. If the agent lacks this info, LlamaIndex prompts the user to supply the missing details.

Yes, you can pass an allowed tools filter list during initialization to expose only specific endpoints. This lets you block sensitive financial tools while keeping lead tools active.

Your roofing payment records and job details are never stored on external servers during indexing. All data passes through secure, encrypted local memory buffers and ephemeral V8 sandboxes.

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