Moka HR MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Moka HR as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Moka HR. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Moka HR?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Moka HR MCP Server
Empower your AI agent to orchestrate your recruitment lifecycle with Moka HR, the premier applicant tracking system for modern high-growth companies. By connecting Moka to your agent, you transform complex candidate tracking, job management, and interview coordination into a natural conversation. Your agent can instantly list open positions, retrieve candidate profiles, monitor interview schedules, and even provide recruitment summaries without you needing to navigate the complex Moka dashboard. Whether you are a hiring manager or a recruiter, your agent acts as a real-time talent assistant, keeping your hiring pipeline organized and your recruitment process efficient.
LlamaIndex agents combine Moka HR tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Job Orchestration — List all active job postings and retrieve detailed requirements for any position.
- Candidate Management — Browse recruitment pipelines and manage candidate profiles, including contact details and history.
- Interview Tracking — Monitor scheduled interviews and retrieve session details instantly.
- Application Control — Manage the relationship between candidates and specific job applications.
- Hiring Insights — Retrieve high-level summaries of recruitment activity and pipeline statistics.
The Moka HR MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Moka HR to LlamaIndex via MCP
Follow these steps to integrate the Moka HR MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Moka HR
Why Use LlamaIndex with the Moka HR MCP Server
LlamaIndex provides unique advantages when paired with Moka HR through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Moka HR tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Moka HR tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Moka HR, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Moka HR tools were called, what data was returned, and how it influenced the final answer
Moka HR + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Moka HR MCP Server delivers measurable value.
Hybrid search: combine Moka HR real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Moka HR to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Moka HR for fresh data
Analytical workflows: chain Moka HR queries with LlamaIndex's data connectors to build multi-source analytical reports
Moka HR MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Moka HR to LlamaIndex via MCP:
create_candidate
Add new candidate
get_application
Get application details
get_candidate
Get candidate details
get_hiring_summary
Get recruitment summary
get_interview
Get interview details
get_job
Get job details
list_applications
List job applications
list_candidates
List candidates
list_interviews
List scheduled interviews
list_jobs
List open job positions
Example Prompts for Moka HR in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Moka HR immediately.
"List all open job positions in our organization."
"Show me the recruitment pipeline for candidate 'Mario'."
"Get a summary of our hiring activity for this month."
Troubleshooting Moka HR MCP Server with LlamaIndex
Common issues when connecting Moka HR to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMoka HR + LlamaIndex FAQ
Common questions about integrating Moka HR MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Moka HR with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Moka HR to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.