Can I create new forms and manage submissions through the AI agent?

Yes. Use `create_form` to build new forms, `list_forms` to see all forms, `list_records` to browse submissions, and `get_record` to inspect individual responses with full field data. Use `delete_form` to remove unused forms.

Can I use templates to create forms faster?

Yes. Use `list_templates` to browse available form templates and `get_template` to inspect their structure. Templates provide reusable form designs that save time on repetitive form creation.

Can I access files attached to form submissions?

Yes. Use `list_files` to retrieve all files attached to form submissions. Each file includes metadata like name, size, and the record it belongs to.

INSTANT PLUG AND PLAY

Indy MCP Server for CrewAIGive CrewAI instant access to 12 tools to Create Form, Create Webhook, Delete Form, and more

Name: Indy
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Indy app connector for CrewAI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Indy Specialist",
    goal="Help users interact with Indy effectively",
    backstory=(
        "You are an expert at leveraging Indy 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 Indy "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

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 Indy MCP Server

Connect your Indy account to any AI agent and manage forms and records through natural conversation.

When paired with CrewAI, Indy becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Indy 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

Form Management — List all forms, inspect configurations, create new forms, and delete unused ones
Record Tracking — Browse all form submissions, inspect individual records with full field data
Template Management — List and inspect form templates for reusable designs
Group Organization — Browse form groups for organized management
File Access — List files attached to form submissions

The Indy MCP Server exposes 12 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.

All 12 Indy tools available for CrewAI

When CrewAI connects to Indy through Vinkius, your AI agent gets direct access to every tool listed below — spanning form-builder, data-collection, freelance-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_form

Create a new form

create_webhook

Create a new webhook

delete_form

Delete a form

delete_webhook

Delete a webhook

get_account_info

Get account status

get_form

Get form details

get_record

Get submission details

get_user

Get user details

list_forms

List all forms

list_records

List form submissions

list_users

List connected users

list_webhooks

List active webhooks

Connect Indy to CrewAI via MCP

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

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 12 tools from Indy

Why Use CrewAI with the Indy MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Indy 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

Indy + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Indy 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 Indy, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Indy 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 Indy against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Indy in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Indy immediately.

"Show all forms and the latest submissions for the 'Customer Feedback' form."

"Create a new 'Event Registration' form and list available templates."

"Show all records for the bug report form and any attached files."

Troubleshooting Indy MCP Server with CrewAI

Common issues when connecting Indy 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.

Indy + CrewAI FAQ

Common questions about integrating Indy 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.