Workable MCP Server for LlamaIndexGive LlamaIndex instant access to 7 tools to Create Candidate, Get Candidate Profile, Get Job Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Workable 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 Workable app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 7 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 Workable. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in Workable?"
)
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 Workable MCP Server
Connect your Workable recruiting account to any AI agent and simplify how you manage your hiring pipelines, track candidates, and coordinate with your team through natural conversation.
LlamaIndex agents combine Workable tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Job Management — List all active and archived job openings and retrieve detailed job descriptions and requirements.
- Candidate Tracking — List and inspect candidates across all jobs, and drill down into specific profiles for experience and status.
- Direct Sourcing — Programmatically register new candidates to specific job openings to accelerate your hiring process.
- Team Coordination — List account members and recruiters to understand your hiring team structure.
- Ecosystem Overview — List linked accounts and verify your Workable instance configuration via AI.
The Workable MCP Server exposes 7 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 7 Workable tools available for LlamaIndex
When LlamaIndex connects to Workable through Vinkius, your AI agent gets direct access to every tool listed below — spanning applicant-tracking, hiring-workflow, candidate-screening, 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.
Register a new candidate to a job
Get details for a specific candidate
Get details for a specific job
List hiring team members
List candidates across all jobs
List active job openings
List connected accounts
Connect Workable to LlamaIndex via MCP
Follow these steps to wire Workable 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 Workable MCP Server
LlamaIndex provides unique advantages when paired with Workable through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Workable tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Workable tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Workable, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Workable tools were called, what data was returned, and how it influenced the final answer
Workable + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Workable MCP Server delivers measurable value.
Hybrid search: combine Workable real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Workable 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 Workable for fresh data
Analytical workflows: chain Workable queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Workable in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Workable immediately.
"List all active job openings in our Workable account."
"Show me the details for the candidate 'John Smith'."
"Add 'Jane Doe' (jane.doe@example.com) as a candidate for the job 'ENG-101'."
Troubleshooting Workable MCP Server with LlamaIndex
Common issues when connecting Workable to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpWorkable + LlamaIndex FAQ
Common questions about integrating Workable MCP Server with LlamaIndex.