How to Use the Manatal MCP in LlamaIndex

Q: Will LlamaIndex search across all Manatal records?

Yes. You define the ingestion process to pull from listcandidates and listjobs so your index covers the entire recruitment scope.

Index your Manatal recruitment data into LlamaIndex for semantic search and grounded candidate matching.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Manatal MCP to LlamaIndex

Create your Vinkius account to connect Manatal 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.

GDPR Free for Subscribers

Setup Manatal with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Semantic search for Manatal in LlamaIndex

Pipe `list_candidates` output into your vector store to build a searchable knowledge base of your talent pool. You no longer need to remember names; just search by skill or experience. Your index updates as you query, ensuring that your agent always references the latest records. This turns your static ATS data into a dynamic research tool.

Ground LlamaIndex answers in Manatal data

Use `get_job` to index current requirements alongside candidate profiles. When you ask about talent gaps, your agent pulls from this grounded knowledge base instead of hallucinating. This prevents the common issue of AI guessing about job statuses. Every answer is backed by the actual state returned by the API.

Query historical applications in LlamaIndex

Load `list_applications` into your document index to analyze past hiring trends. Your agent can compare current performance against historical data points indexed from your account. Retrieve deep insights using `get_application` to see notes and status changes. This gives you a clear picture of why certain hires succeeded or failed.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Manatal. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Manatal now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Manatal MCP in LlamaIndex

You use the MCP tool spec to fetch data, which LlamaIndex then converts into nodes for your vector store. This turns raw API responses into queryable knowledge.

Yes. You define the ingestion process to pull from `list_candidates` and `list_jobs` so your index covers the entire recruitment scope.

The server operates in a zero-trust sandbox. Your candidate records are only accessed when you trigger a tool call and are never shared with external parties.

By indexing your tool outputs, you create a history of your recruitment activities. You can query these past findings to see how your candidate pool has evolved.

It accesses candidate profiles, job descriptions, and application statuses. Every request is isolated and authenticated via your single endpoint token.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript