How to Use the Adzuna MCP in LlamaIndex

Q: How do I initialize the Adzuna MCP tools in LlamaIndex?

Install llama-index-tools-mcp and set up a BasicMCPClient. Wrap it with McpToolSpec and pass the async tool list directly to your FunctionAgent.

Q: Does the Adzuna MCP Server support data access filtering?

You control exactly what gets exposed. Use the allowedtools filter during setup to restrict your LlamaIndex agent to just the company listing endpoint if needed.

Index live global job listings and salary trends directly into your LlamaIndex RAG applications using this Adzuna MCP integration.

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Connect Adzuna MCP to LlamaIndex

Create your Vinkius account to connect Adzuna 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 Adzuna with LlamaIndex

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Indexing MCP Server job listings

Stop relying on stale static documents for your hiring insights. By passing `search_jobs` through `McpToolSpec`, your LlamaIndex application pulls live, country-specific vacancies and immediately embeds them into your vector store. This turns raw API responses into a persistent, searchable knowledge base. When a user asks about software engineering roles in the UK, the system retrieves actual, current job descriptions rather than hallucinating outdated market conditions.

RAG pipelines for compensation

You can build specialized indexes around the `get_salary_history` and `get_salary_histogram` endpoints of the MCP Server. The agent fetches the distribution data for specific titles and stores the exact numerical trends alongside your internal HR documents. Querying this data happens instantly. A user asks the index to compare a candidate's salary expectation, and LlamaIndex grounds its answer in the real-world compensation metrics it just pulled from the market.

Tracking top hiring employers

Connect `list_top_companies` to automatically map out which organizations dominate specific sectors. The agent grabs the employer list based on your keyword and feeds it into the document index. You build a unified view of industry movement. Combine these live company lists with news articles in your vector store, allowing your system to cross-reference hiring spikes with recent funding announcements.

Setup guide

Set up Adzuna 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 Adzuna 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 Adzuna tools.",
)
response = await agent.run("List recent Adzuna data")

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Common questions about Adzuna MCP in LlamaIndex

Install `llama-index-tools-mcp` and set up a `BasicMCPClient`. Wrap it with `McpToolSpec` and pass the async tool list directly to your `FunctionAgent`.

Yes, it stores the exact outputs. The response from the histogram tool gets embedded into your vector store, letting you run semantic searches against those distributions later without hitting the API again.

You control exactly what gets exposed. Use the `allowed_tools` filter during setup to restrict your LlamaIndex agent to just the company listing endpoint if needed.

LlamaIndex reads the schema provided by the server. It knows `search_jobs` requires a 2-letter country code and prompts the user if that information is missing from the initial query.

Vinkius routes traffic through zero-trust ephemeral environments. The specific job categories, country codes, and salary ranges you index are processed in memory and wiped immediately after the response is sent.

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