Finch MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Finch 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 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 Finch. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Finch?"
)
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 Finch MCP Server
Finch is the unified API for HRIS and payroll. This MCP server allows your AI agent to interact with various HR and payroll providers through a single integration flawlessly.
LlamaIndex agents combine Finch tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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.
Key Features
- Directory Orchestration — List all employees in the connected organization and fetch detailed profiles natively.
- Employment Intelligence — Retrieve granular employment data including job titles, departments, and compensation flawlessly.
- Payroll Transparency — Access pay groups and individual pay statements to monitor payroll data synchronously.
- Connection Introspection — Check the status, provider, and authorized permissions for any connection flawlessly native.
- Automated Job Tracking — Monitor data sync jobs to ensure your HRIS data is always up to date flawlessly through the agent.
- Provider Discovery — List all supported HRIS and payroll providers to verify integration compatibility flawlessly.
The Finch MCP Server exposes 11 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 Finch to LlamaIndex via MCP
Follow these steps to integrate the Finch 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 11 tools from Finch
Why Use LlamaIndex with the Finch MCP Server
LlamaIndex provides unique advantages when paired with Finch through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Finch tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Finch tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Finch, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Finch tools were called, what data was returned, and how it influenced the final answer
Finch + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Finch MCP Server delivers measurable value.
Hybrid search: combine Finch real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Finch 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 Finch for fresh data
Analytical workflows: chain Finch queries with LlamaIndex's data connectors to build multi-source analytical reports
Finch MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Finch to LlamaIndex via MCP:
get_automated_job
Get details for a specific automated job
get_company
Get organization data (legal name, EIN, primary address)
get_employment
Get employment data for an individual (title, salary, department, etc.)
get_individual
Get personal data for an individual (name, email, SSN, etc.)
get_me
Get details for the authorized application/user connection
introspect
Check the status and permissions of the current connection
list_automated_jobs
List automated data sync jobs
list_directory
Read the employee directory for the connected organization
list_pay_groups
List pay groups for the organization
list_pay_statements
List pay statements for a specific payment ID
list_supported_providers
List all HRIS/Payroll providers supported by Finch
Example Prompts for Finch in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Finch immediately.
"List all employees in the directory."
"Check the status of my connection to Gusto."
"List pay statements for payment ID pmt_123."
Troubleshooting Finch MCP Server with LlamaIndex
Common issues when connecting Finch to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFinch + LlamaIndex FAQ
Common questions about integrating Finch 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 Finch 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 Finch to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.