How to Use the BunnyDoc MCP in CrewAI

Q: Can a CrewAI agent draft BunnyDoc signature requests autonomously?

Yes. An agent can use listtemplates to find the correct document form, then call createsignaturerequest to send the envelope to the client.

Q: Can I limit which BunnyDoc tools my CrewAI agents can access?

Yes. You can use the MCPServerHTTP class with a custom tool filter to only expose safe tools like listenvelopes while restricting administrative actions.

Deploy a team of autonomous agents to manage your BunnyDoc signature pipelines with CrewAI.

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Connect BunnyDoc MCP to CrewAI

Create your Vinkius account to connect BunnyDoc to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup BunnyDoc with CrewAI

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Coordinate document audits using CrewAI and this MCP Server

The `list_envelopes` tool retrieves a complete history of all signature requests sent from your account. In a CrewAI setup, an Auditor agent calls this tool to gather pending documents while a separate Coordinator agent matches them against your client database. This multi-agent collaboration runs entirely in the background. Your agents pass data back and forth, flagging unsigned contracts and preparing status summaries without any human intervention.

Automate team onboarding and access control

The `add_team_member` tool sends out platform invitations to join your signing workspace. Your CrewAI HR agent can trigger this action the moment a new employee contract status returns as completed. By combining this with `list_team_members`, your crew of agents uses the MCP Server to audit your roster every week. They will identify inactive accounts and alert your administrator to remove them, keeping your workspace clean.

Analyze document usage and template performance

The `get_usage_stats` tool pulls detailed metrics on how many documents your team has sent and signed. A specialized analyst agent reads this data alongside `list_templates` to determine which signing forms are used most frequently. The agent then compiles a markdown report detailing template efficiency. This allows your team to archive obsolete forms and focus resources on the templates that convert signers fastest.

Setup guide

Set up BunnyDoc MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke BunnyDoc tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="BunnyDoc Analyst",
    goal="Access and analyze BunnyDoc data via MCP.",
    backstory="Expert analyst with direct BunnyDoc access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent BunnyDoc transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="BunnyDoc Analyst",
        goal="Access and analyze BunnyDoc data via MCP.",
        backstory="Expert analyst with direct BunnyDoc access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent BunnyDoc transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BunnyDoc. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about BunnyDoc MCP in CrewAI

Pass your Vinkius server URL directly into the agent's MCP configuration. CrewAI automatically discovers all ten tools and exposes them to the designated agent.

Yes. An agent can use `list_templates` to find the correct document form, then call `create_signature_request` to send the envelope to the client.

Agents share context through CrewAI's memory system. If one agent calls `get_envelope_status`, the resulting status is available to the rest of the crew for subsequent tasks.

Yes. You can use the `MCPServerHTTP` class with a custom tool filter to only expose safe tools like `list_envelopes` while restricting administrative actions.

Your team list and account details remain stored on BunnyDoc's secure servers. The MCP Server acts as an ephemeral bridge, passing requested metadata to your local CrewAI environment without caching any personal data.

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