Greenhouse MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Advance Application, Create Candidate, Get Api Status, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Greenhouse as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Greenhouse app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Greenhouse. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Greenhouse?"
)
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 Greenhouse MCP Server
Connect your Greenhouse account to any AI agent and take full control of your hiring pipeline and recruitment workflows through natural conversation.
LlamaIndex agents combine Greenhouse tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through 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
- Candidate Orchestration — List and manage candidate records programmatically, including contact info, current company, and professional titles
- Application Lifecycle — Monitor job applications and take immediate action by advancing candidates to the next stage or marking rejections with reasons
- Job Management — Access detailed metadata for all active job openings, including hiring teams and department structures
- Organizational Visibility — Retrieve complete company department lists and office locations to coordinate recruitment logistics
- System Monitoring — Check API connectivity and Harvest API status directly through your agent for reliable data operations
The Greenhouse MCP Server exposes 12 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.
All 12 Greenhouse tools available for LlamaIndex
When LlamaIndex connects to Greenhouse through Vinkius, your AI agent gets direct access to every tool listed below — spanning candidate-tracking, hiring-pipeline, talent-acquisition, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Move candidate to next stage
Can include first name, last name, and company. Add new candidate
Get account connectivity
Get candidate info
Get job metadata
List job applications
List recruitment candidates
List company departments
List office locations
List active job openings
Requires a reason ID. Reject job application
Modify candidate info
Connect Greenhouse to LlamaIndex via MCP
Follow these steps to wire Greenhouse into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Greenhouse MCP Server
LlamaIndex provides unique advantages when paired with Greenhouse through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Greenhouse tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Greenhouse tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Greenhouse, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Greenhouse tools were called, what data was returned, and how it influenced the final answer
Greenhouse + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Greenhouse MCP Server delivers measurable value.
Hybrid search: combine Greenhouse real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Greenhouse 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 Greenhouse for fresh data
Analytical workflows: chain Greenhouse queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Greenhouse in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Greenhouse immediately.
"Find candidate with email 'candidate@example.com' and show their status."
"List all active job openings for the 'Engineering' department."
"Advance application ID 'app_987' to the next stage."
Troubleshooting Greenhouse MCP Server with LlamaIndex
Common issues when connecting Greenhouse to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGreenhouse + LlamaIndex FAQ
Common questions about integrating Greenhouse MCP Server with LlamaIndex.