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 LangChain 8 tools — connect in under 2 minutes

Name: Loopio
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Loopio through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "loopio": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Loopio, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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.

LangChain's ecosystem of 500+ components combines seamlessly with Loopio through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the Loopio MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Loopio via MCP

Why Use LangChain with the Loopio MCP Server

LangChain provides unique advantages when paired with Loopio through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Loopio MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Loopio queries for multi-turn workflows

Loopio + LangChain Use Cases

Practical scenarios where LangChain combined with the Loopio MCP Server delivers measurable value.

RAG with live data: combine Loopio tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Loopio, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Loopio tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Loopio tool call, measure latency, and optimize your agent's performance

Loopio MCP Tools for LangChain (8)

These 8 tools become available when you connect Loopio to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Loopio to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Loopio + LangChain FAQ

Common questions about integrating Loopio MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.