How to Use the Merge (Unified Integration API) MCP in LlamaIndex

Q: How do I convert Merge (Unified Integration API) outputs into LlamaIndex documents?

You wrap the tool outputs from listemployees or listcandidates using the MCP tool spec. The framework converts the returned JSON payloads into searchable document nodes automatically.

Q: Can I use Merge (Unified Integration API) with LlamaIndex sub-question query engines?

Yes, you can register tools like listtickets and listcompanies as tools for a sub-question engine. The engine splits complex queries into individual API calls across your integrations.

Index unified HRIS, ATS, and ticketing data into LlamaIndex vector stores for grounded RAG.

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Connect Merge (Unified Integration API) MCP to LlamaIndex

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Setup Merge (Unified Integration API) with LlamaIndex

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Index candidate and employee data for semantic search

The `list_candidates` and `list_employees` tools fetch live talent and workforce records directly into your LlamaIndex pipelines using this MCP connection. Instead of just reading the raw text, the framework indexes these records into a vector store for semantic retrieval. Your agent queries this index to find employees with specific skill sets or candidates matching a job description. The answers are grounded in actual HRIS and ATS data, eliminating hallucinations.

Build a queryable knowledge base using this MCP Server

The `list_tickets` and `list_contacts` tools pull support histories and customer profiles into your LlamaIndex documents. This live data is automatically converted into nodes that your query engine can search. When a customer submits a new query, your agent searches past tickets to find similar resolutions. You build a self-updating support index without setting up complex ETL pipelines.

Map integration boundaries to prevent indexing errors

The `get_account_details` tool identifies active integration boundaries and status limits before you run a data sync. Your LlamaIndex agent checks these details to ensure you only index active, healthy customer accounts. By filtering out paused integrations via `list_accounts` or `list_companies`, you avoid polluting your vector database with stale or incomplete metadata. Your search index stays clean and accurate.

Setup guide

Set up Merge (Unified Integration API) 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 Merge (Unified Integration API) 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 Merge (Unified Integration API) tools.",
)
response = await agent.run("List recent Merge (Unified Integration API) data")

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Common questions about Merge (Unified Integration API) MCP in LlamaIndex

You wrap the tool outputs from `list_employees` or `list_candidates` using the MCP tool spec. The framework converts the returned JSON payloads into searchable document nodes automatically.

Yes, you can register tools like `list_tickets` and `list_companies` as tools for a sub-question engine. The engine splits complex queries into individual API calls across your integrations.

Yes, the server exposes resources that your LlamaIndex agent can load directly into memory. This lets you read raw schemas without invoking individual tool calls.

Use the allowed tools filter when initializing your tool spec. You can expose only `list_employees` for HRIS workflows while keeping ATS and CRM tools hidden.

All fetched contact records and support tickets are processed in transit inside a secure, ephemeral V8 isolate. Authentication credentials are encrypted at rest and never exposed during the vector indexing process.

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