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 LangChain 10 tools — connect in under 2 minutes

Name: BunnyDoc
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect BunnyDoc 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({
        "bunnydoc": {
            "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 BunnyDoc, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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Ed25519Audit chain

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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.

LangChain's ecosystem of 500+ components combines seamlessly with BunnyDoc through native MCP adapters. Connect 10 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

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 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 BunnyDoc to LangChain via MCP

Follow these steps to integrate the BunnyDoc 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 10 tools from BunnyDoc via MCP

Why Use LangChain with the BunnyDoc MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine BunnyDoc 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 BunnyDoc queries for multi-turn workflows

BunnyDoc + LangChain Use Cases

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

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

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

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

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

BunnyDoc MCP Tools for LangChain (10)

These 10 tools become available when you connect BunnyDoc to LangChain 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 LangChain

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

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

BunnyDoc + LangChain FAQ

Common questions about integrating BunnyDoc 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.