JobScore 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 JobScore as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 JobScore. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in JobScore?"
)
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 JobScore MCP Server
Empower your AI agents with JobScore's comprehensive applicant tracking system. This MCP server allows you to list and retrieve job postings, track candidates, manage hiring teams and departments, and view hiring sources directly through the JobScore API. Ideal for automating recruitment workflows and talent acquisition.
LlamaIndex agents combine JobScore tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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.
The JobScore 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 JobScore to LlamaIndex via MCP
Follow these steps to integrate the JobScore 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 JobScore
Why Use LlamaIndex with the JobScore MCP Server
LlamaIndex provides unique advantages when paired with JobScore through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine JobScore tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain JobScore tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query JobScore, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what JobScore tools were called, what data was returned, and how it influenced the final answer
JobScore + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the JobScore MCP Server delivers measurable value.
Hybrid search: combine JobScore real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query JobScore 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 JobScore for fresh data
Analytical workflows: chain JobScore queries with LlamaIndex's data connectors to build multi-source analytical reports
JobScore MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect JobScore to LlamaIndex via MCP:
get_candidate
Returns contact history, resume highlights (if available), and current application status. Use this before an interview or when evaluating an applicant. Retrieves details for a specific candidate
get_job
Includes job descriptions, requirements, and hiring team identifiers. Use this to provide detailed information about a specific opening. Retrieves details for a specific job
get_me
Use this to verify connection status and identity. Gets current authenticated user info
list_candidates
Includes candidate names, current stage, and IDs. Essential for monitoring the talent pool and identifying new applications. Lists all candidates
list_departments
g., Engineering, Marketing) used to categorize jobs in JobScore. Useful for filtering hiring data by business unit. Lists all departments
list_hiring_teams
Useful for identifying recruiters and hiring managers associated with specific jobs. Lists all hiring teams
list_jobs
Returns job titles, IDs, and departments. Use this to identify active positions or find a job ID for candidate management. Lists all jobs in JobScore
list_locations
Useful for understanding the geographical scope of hiring efforts. Lists all office locations
list_sources
g., "LinkedIn", "Referral", "Job Board") from which candidates are originating. Essential for analyzing the effectiveness of hiring channels. Lists all candidate sources
list_users
Useful for identifying team members and their roles. Lists all users in the account
Example Prompts for JobScore in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with JobScore immediately.
"List all open jobs in JobScore."
"Show me the details for candidate ID '789'."
"Check the hiring team for the 'Software Engineer' job."
Troubleshooting JobScore MCP Server with LlamaIndex
Common issues when connecting JobScore to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpJobScore + LlamaIndex FAQ
Common questions about integrating JobScore 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?
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Connect JobScore to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.