How do I get an Onboard.io API Key?

You can find your API key in the Onboard.io dashboard under Settings > API. This token is used for Bearer authentication.

Can I see internal comments on a plan?

Yes! Use the `list_plan_comments` tool with a specific Plan ID to retrieve the discussion history and internal notes for that implementation.

What progress metrics are available?

The `get_plan_progress_analytics` tool provides health scores, percent complete, and overview stats for your launch plans.

Onboard.io Implementation MCP Server for LlamaIndex 10 tools — connect in under 2 minutes

Name: Onboard.io Implementation
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Onboard.io Implementation as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Onboard.io Implementation. "
            "You have 10 tools available."
        ),
    )

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

asyncio.run(main())

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About Onboard.io Implementation MCP Server

Connect your Onboard.io account to your AI agent and streamline your customer implementation and onboarding workflows through natural conversation and real-time project tracking.

LlamaIndex agents combine Onboard.io Implementation 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.

What you can do

Launch Plan Oversight — List all active customer implementation plans and retrieve detailed progress and metadata.
Task Management — Access all tasks and milestones associated with specific plans and check their assignments and due dates.
Customer Monitoring — List and inspect profiles for all customer accounts currently in the onboarding phase.
Team Collaboration — View internal team members and specialists assigned to your onboarding projects.
Communication Tracking — Retrieve a history of discussion and internal comments for any launch plan.
Progress Analytics — Fetch high-level health metrics and percent-complete stats for your implementation workflows.
Deep Inspection — Fetch complete metadata for specific plans, tasks, or customers using their unique IDs.

The Onboard.io Implementation 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 Onboard.io Implementation to LlamaIndex via MCP

Follow these steps to integrate the Onboard.io Implementation 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 Onboard.io Implementation

Why Use LlamaIndex with the Onboard.io Implementation MCP Server

LlamaIndex provides unique advantages when paired with Onboard.io Implementation through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Onboard.io Implementation tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Onboard.io Implementation tool calls with transformations, filters, and re-rankers in a typed pipeline

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

Observability integrations show exactly what Onboard.io Implementation tools were called, what data was returned, and how it influenced the final answer

Onboard.io Implementation + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Onboard.io Implementation MCP Server delivers measurable value.

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

Data enrichment: query Onboard.io Implementation 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 Onboard.io Implementation for fresh data

Analytical workflows: chain Onboard.io Implementation queries with LlamaIndex's data connectors to build multi-source analytical reports

Onboard.io Implementation MCP Tools for LlamaIndex (10)

These 10 tools become available when you connect Onboard.io Implementation to LlamaIndex via MCP:

get_member_details

Get team member profile

get_onboarding_customer_details

Get customer profile info

get_plan_details

Get specific plan info

get_plan_progress_analytics

Get plan health metrics

get_task_details

Get specific task info

list_onboarding_customers

List onboarding customers

list_onboarding_plans

List all implementation plans

list_plan_comments

List plan collaboration comments

list_plan_tasks

List onboarding tasks

list_team_members

io. List onboarding team members

Example Prompts for Onboard.io Implementation in LlamaIndex

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

"List all our active onboarding plans."

"What is the status of the 'API Integration' task in plan 'plan_98765'?"

"Show me the health metrics for the 'Enterprise Launch' project."

Troubleshooting Onboard.io Implementation MCP Server with LlamaIndex

Common issues when connecting Onboard.io Implementation to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Onboard.io Implementation + LlamaIndex FAQ

Common questions about integrating Onboard.io Implementation 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 Onboard.io Implementation tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.