How to Use the Bounsel MCP in LlamaIndex

Q: How does LlamaIndex index live Bounsel templates?

The framework calls listtemplates to fetch your active templates and loads them as document nodes. These nodes are indexed into your vector store, allowing semantic search to find the correct template.

Q: Can I query active Bounsel signature statuses using LlamaIndex?

Yes, your agent uses listdocuments to pull the latest statuses and matches them against user queries. The agent retrieves real-time contract states instead of relying on static, outdated vector data.

Q: Can this setup handle large volumes of contracts?

Yes, the MCP Server supports paging through listdocuments to build a complete index of your legal pipeline. LlamaIndex processes these records into chunks for efficient vector retrieval.

Index your Bounsel contracts and templates into LlamaIndex to query active legal pipelines with semantic search.

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Connect Bounsel MCP to LlamaIndex

Create your Vinkius account to connect Bounsel to LlamaIndex 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 Bounsel with LlamaIndex

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Index Bounsel contract metadata in LlamaIndex

The `list_documents` tool retrieves your entire contract catalog so LlamaIndex can index the metadata for semantic search queries. Instead of searching by exact filename, your agent queries your contract database using natural language to find specific agreements. This MCP Server allows your RAG pipeline to pull fresh document details using `get_document` on demand. Your queries are grounded in active contract data, eliminating hallucinations about signed agreements.

Build a queryable template library via MCP Server

The `list_templates` tool fetches your smart legal templates and converts their structures into queryable document nodes. LlamaIndex maps out which templates require specific variables, making it easy for your agent to select the correct form. When a user asks how to draft a specific agreement, the agent calls `get_template` to pull the exact schema. It then feeds those requirements back to the user or fills them automatically using indexed company data.

Context-aware contract generation in LlamaIndex

The `create_document` tool generates new legal documents using context retrieved from your vector stores. LlamaIndex pulls relevant customer data from your knowledge base and feeds it directly into the template variables. Once created, the agent calls `send_document` to start the signing process. The entire transaction is indexed, allowing your agent to confirm that the specific contract was drafted and sent.

Setup guide

Set up Bounsel MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Bounsel MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Bounsel tools.",
)
response = await agent.run("List recent Bounsel data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bounsel. 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 Bounsel MCP in LlamaIndex

The framework calls `list_templates` to fetch your active templates and loads them as document nodes. These nodes are indexed into your vector store, allowing semantic search to find the correct template.

Yes, your agent uses `list_documents` to pull the latest statuses and matches them against user queries. The agent retrieves real-time contract states instead of relying on static, outdated vector data.

Your LlamaIndex pipeline queries your vector store for customer details and passes those values to `create_document`. The MCP Server handles the API translation to generate the contract with the correct parameters.

Yes, the MCP Server supports paging through `list_documents` to build a complete index of your legal pipeline. LlamaIndex processes these records into chunks for efficient vector retrieval.

Your contract text and template fields remain within your secure Bounsel account and local LlamaIndex vector store. The MCP Server acts as a stateless conduit, ensuring your legal drafts are never cached on external servers.

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