What authentication does Loopio require and where do I get my token?

Loopio uses OAuth2 with Bearer token authentication. You need to generate an access token from your Loopio account under Settings -> API. The token provides secure, scoped access to your projects, libraries, and team data.

Can the AI agent search and retrieve approved answers from my Loopio library?

Yes. The search_library tool lets the agent query your master knowledge base using natural language. It searches across question text, answer text, and tags, returning the most relevant approved entries with their full content. This ensures your AI responses are always based on pre-approved, accurate information.

Can I create new RFP projects programmatically through the AI agent?

Absolutely. The create_submission tool allows the agent to spin up new Loopio projects with a name, description, company context, due date, and assigned owner. The project is created in 'Not Started' status and ready for immediate team collaboration and answer drafting.

How do I track the progress of active RFPs across my workspace?

Use list_projects to see all active initiatives with their current status, then drill into any project with get_project to check completion percentage, due dates, and ownership. You can also use list_questionnaires to see every individual question and which ones still need answers.

Loopio MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes

Name: Loopio
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 8 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Loopio through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

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 agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Loopio Assistant",
            instructions=(
                "You help users interact with Loopio. "
                "You have access to 8 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Loopio"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Loopio MCP Server

Connect your Loopio RFP management platform to your AI agent to transform proposal workflows into intelligent, conversational processes.

The OpenAI Agents SDK auto-discovers all 8 tools from Loopio through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Loopio, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Browse Projects — List all your active RFPs, RFIs, and security questionnaires. Check progress, due dates, and completion status at a glance.
Search the Knowledge Library — Query your master library of pre-approved answers. Find exactly what you need before drafting new responses.
Review Questionnaire Responses — Fetch individual questions and their current answers from any project. Track what has been answered and what still needs attention.
Create New Submissions — Spin up new RFP projects instantly with name, deadline, company context, and owner assignment.
Manage Teams — List team members to identify who is available for project assignments and collaboration.

The Loopio MCP Server exposes 8 tools through the Vinkius. Connect it to OpenAI Agents SDK 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 Loopio to OpenAI Agents SDK via MCP

Follow these steps to integrate the Loopio MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 8 tools from Loopio

Why Use OpenAI Agents SDK with the Loopio MCP Server

OpenAI Agents SDK provides unique advantages when paired with Loopio through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Loopio + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Loopio MCP Server delivers measurable value.

Automated workflows: build agents that query Loopio, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Loopio, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Loopio tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Loopio to resolve tickets, look up records, and update statuses without human intervention

Loopio MCP Tools for OpenAI Agents SDK (8)

These 8 tools become available when you connect Loopio to OpenAI Agents SDK via MCP:

create_submission

Requires a project name. Optionally accepts a description, company name, due date, project type, and owner ID. The project will be created in "Not Started" status and ready for team collaboration. Create a new RFP project/submission in Loopio

get_project

Use this to check the state of a specific RFP response. Get details of a specific Loopio project by ID

get_questionnaire_responses

If no entryId is provided, returns all entries and their current responses. Use this to review what answers have been drafted or finalized for RFP questions. Get responses for a specific questionnaire entry or all entries in a project

list_libraries

Each stack contains approved Q&A entries organized by category. Use this to discover which knowledge bases are available for searching. List all library stacks available in Loopio

list_projects

Each project represents an active RFP response or questionnaire. Use this to discover all ongoing and recent response initiatives. Optionally limit results with the limit parameter. List all Loopio projects (RFPs, RFIs, questionnaires) in your workspace

list_questionnaires

Each entry represents a question from an RFP, RFI, or security questionnaire that needs to be answered. Use this to understand the scope of a project and track which questions have been answered. List all questionnaire entries (questions) for a specific Loopio project

list_team_members

Use this to identify who is assigned to projects, find user IDs for assigning project ownership, or understand team composition. List all team members in your Loopio workspace

search_library

This is the primary way to find existing approved responses before drafting new answers. You can refine results with optional filters like tags, category, stack, and whether to search in questions or answers. Always use this before creating new library entries. Search the Loopio knowledge library for approved Q&A entries

Example Prompts for Loopio in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Loopio immediately.

"Search the Loopio library for our approved response about SOC 2 compliance."

"Create a new RFP project called 'Acme Corp Security Assessment' with a deadline of March 15th."

"Show me all open RFP projects and their completion percentage."

Troubleshooting Loopio MCP Server with OpenAI Agents SDK

Common issues when connecting Loopio to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Loopio + OpenAI Agents SDK FAQ

Common questions about integrating Loopio MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.