BunnyDoc MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add BunnyDoc as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to BunnyDoc. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in BunnyDoc?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine BunnyDoc tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the BunnyDoc MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from BunnyDoc
Why Use LlamaIndex with the BunnyDoc MCP Server
LlamaIndex provides unique advantages when paired with BunnyDoc through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine BunnyDoc tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain BunnyDoc tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query BunnyDoc, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what BunnyDoc tools were called, what data was returned, and how it influenced the final answer
BunnyDoc + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the BunnyDoc MCP Server delivers measurable value.
Hybrid search: combine BunnyDoc real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query BunnyDoc to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying BunnyDoc for fresh data
Analytical workflows: chain BunnyDoc queries with LlamaIndex's data connectors to build multi-source analytical reports
BunnyDoc MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect BunnyDoc to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting BunnyDoc to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBunnyDoc + LlamaIndex FAQ
Common questions about integrating BunnyDoc MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect BunnyDoc with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect BunnyDoc to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.