Can I check if a document has been signed using the agent?

Yes! Use the `get_envelope_status` tool with the Envelope ID. Your agent will fetch the current status (e.g., 'Completed' or 'Sent') directly from BunnyDoc.

How do I send a signature request to multiple recipients?

Simply ask the agent to `create_signature_request` and provide the Template ID and a JSON array of recipients. Each object should include the recipient's name and email.

Does the integration allow listing all available templates?

Yes. Use the `list_templates` tool. It will retrieve all the document templates configured in your BunnyDoc account, making it easy to find the ID you need for a new request.

BunnyDoc MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: BunnyDoc
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to BunnyDoc through Vinkius, pass the Edge URL in the `mcps` parameter and every BunnyDoc 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="BunnyDoc Specialist",
    goal="Help users interact with BunnyDoc effectively",
    backstory=(
        "You are an expert at leveraging BunnyDoc 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 BunnyDoc "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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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 BunnyDoc MCP Server

Connect your BunnyDoc account to any AI agent and orchestrate your eSignature workflows, document lifecycle, and team collaboration through natural conversation.

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

Signature Requests — Trigger new document signature requests using pre-defined templates directly from your workspace.
Status Oversight — Monitor the real-time status of envelopes (Draft, Sent, Signed, Completed) using natural language.
Template Management — List all available document templates to ensure consistency in your signing workflows.
Team Coordination — Access your directory of team members and invite new collaborators to the platform.
Webhook Automation — Subscribe to lifecycle events (viewed, signed, completed) to automate your back-office response.
Document Auditing — Retrieve detailed metadata and audit trails for any envelope ID straight from your workspace.

The BunnyDoc MCP Server exposes 10 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 BunnyDoc to CrewAI via MCP

Follow these steps to integrate the BunnyDoc 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 10 tools from BunnyDoc

Why Use CrewAI with the BunnyDoc MCP Server

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

BunnyDoc + CrewAI Use Cases

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

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

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

BunnyDoc MCP Tools for CrewAI (10)

These 10 tools become available when you connect BunnyDoc to CrewAI via MCP:

add_team_member

Invite a new member to the team

create_signature_request

Create a new signature request from a template

get_account_info

Retrieve core account information

get_envelope_status

Get status of a specific signature request (envelope)

get_usage_stats

Retrieve API usage statistics

list_envelopes

List all signature requests

list_team_members

List all members of the team

list_templates

List all available document templates

subscribe_webhook

Subscribe to signature events via webhook

unsubscribe_webhook

Remove a webhook subscription

Example Prompts for BunnyDoc in CrewAI

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

"List all my document templates in BunnyDoc."

"Show the status of signature request env_99283."

"Send the 'NDA' template to Jane Smith (jane@example.com)."

Troubleshooting BunnyDoc MCP Server with CrewAI

Common issues when connecting BunnyDoc 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.

BunnyDoc + CrewAI FAQ

Common questions about integrating BunnyDoc 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.