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 CrewAI 8 tools — connect in under 2 minutes

Name: Loopio
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Loopio through Vinkius, pass the Edge URL in the `mcps` parameter and every Loopio tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Loopio Specialist",
    goal="Help users interact with Loopio effectively",
    backstory=(
        "You are an expert at leveraging Loopio tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Loopio "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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60%Token savings

High SecurityEnterprise-grade

IAMAccess control

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DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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.

When paired with CrewAI, Loopio becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Loopio tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 8 tools from Loopio

Why Use CrewAI with the Loopio MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Loopio through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Loopio + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Loopio for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Loopio, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Loopio tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Loopio against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Loopio MCP Tools for CrewAI (8)

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

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

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Loopio + CrewAI FAQ

Common questions about integrating Loopio MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.