Onfido MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Applicant, Create Check, Create Workflow Run, and more

Name: Onfido
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Onfido 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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The Onfido MCP Server for LlamaIndex is a standout in the Human Resources category — giving your AI agent 6 tools to work with, ready to go from day one.

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python

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 Onfido. "
            "You have 6 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Onfido?"
    )
    print(response)

asyncio.run(main())

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About Onfido MCP Server

Connect your Onfido account to any AI agent to streamline your KYC (Know Your Customer) and identity verification processes through natural conversation.

LlamaIndex agents combine Onfido tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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

Applicant Management — Create and manage applicant profiles representing individuals undergoing verification.
Workflow Studio Integration — Start and monitor complex verification workflows (Workflow Runs) to automate multi-step identity checks.
Legacy Checks — Create classic checks for specific report combinations like document verification and facial similarity.
Detailed Reporting — Retrieve comprehensive verification reports, including results and granular breakdowns of identity data.
Real-time Notifications — Register webhooks to receive asynchronous updates on verification statuses directly to your systems.

The Onfido MCP Server exposes 6 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Onfido tools available for LlamaIndex

When LlamaIndex connects to Onfido through Vinkius, your AI agent gets direct access to every tool listed below — spanning identity-verification, kyc, applicant-screening, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create applicant on Onfido

Create a new Onfido applicant

create

Create check on Onfido

Create a new Check (Legacy/Classic)

create

Create workflow run on Onfido

Create a new Workflow Run

get

Get report on Onfido

Retrieve a Verification Report

get

Get workflow run on Onfido

g., awaiting_input, processing, approved, review, declined). Retrieve a Workflow Run

Register webhook on Onfido

Connect Onfido to LlamaIndex via MCP

Follow these steps to wire Onfido into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 6 tools from Onfido

Why Use LlamaIndex with the Onfido MCP Server

LlamaIndex provides unique advantages when paired with Onfido through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Onfido tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Onfido tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Onfido, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Onfido tools were called, what data was returned, and how it influenced the final answer

Onfido + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Onfido MCP Server delivers measurable value.

Hybrid search: combine Onfido real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Onfido 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 Onfido for fresh data

Analytical workflows: chain Onfido queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Onfido in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Onfido immediately.

"Create a new Onfido applicant for John Doe (john.doe@example.com)."

"Start a verification workflow 'wf_abc' for applicant 'app_12345'."

"Retrieve the details for report ID 'rep_xyz789'."

Troubleshooting Onfido MCP Server with LlamaIndex

Common issues when connecting Onfido to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Onfido + LlamaIndex FAQ

Common questions about integrating Onfido MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Onfido tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.