How to Use the Better Proposals MCP in LlamaIndex

Q: Can LlamaIndex create new Better Proposals documents?

Yes. While RAG is the primary focus, the createproposal tool allows your FunctionAgent to draft new pitches based on the indexed knowledge base.

Q: Does the agent need access to all Better Proposals tools?

No. You restrict access using the allowedtools filter. A pure read-only RAG setup only needs getproposal and getcompany.

Index your Better Proposals data into searchable LlamaIndex knowledge bases.

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Connect Better Proposals MCP to LlamaIndex

Create your Vinkius account to connect Better Proposals 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 Better Proposals with LlamaIndex

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Grounded RAG with Proposal Data

This MCP Server connects your LlamaIndex application directly to Better Proposals. Instead of just firing off actions, your app indexes the output of `list_proposals` and `get_proposal` into a vector store. Users query past pitches using natural language. The system pulls actual API data rather than guessing at pricing or terms from outdated PDFs.

LlamaIndex MCP Server Setup

Install `llama-index-tools-mcp` and point `BasicMCPClient` to your Vinkius URL. Wrap it with `McpToolSpec` to expose tools like `get_analytics` and `list_companies`. Pass these tools to a `FunctionAgent`. You filter access using the `allowed_tools` parameter, ensuring your RAG app only reads what it needs to build the index.

Semantic Search for Sales Analytics

Raw viewer metrics are hard to parse manually. Your agent calls `get_analytics` across multiple documents and embeds the results. You ask the agent which pitch format closed fastest last quarter. It searches the indexed tool outputs, cross-references `list_templates`, and returns a grounded answer based on real conversion data.

Setup guide

Set up Better Proposals 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 Better Proposals 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 Better Proposals tools.",
)
response = await agent.run("List recent Better Proposals 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 Better Proposals. 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 Better Proposals MCP in LlamaIndex

Connect the MCP client and pass the tools to your agent. The agent uses `list_proposals` to fetch raw data and indexes it for your semantic search queries.

Yes. While RAG is the primary focus, the `create_proposal` tool allows your `FunctionAgent` to draft new pitches based on the indexed knowledge base.

The Vinkius endpoint manages the connection state. Your application should still implement backoff logic when running heavy indexing jobs across `list_contacts`.

No. You restrict access using the `allowed_tools` filter. A pure read-only RAG setup only needs `get_proposal` and `get_company`.

Vinkius routes your API calls through a stateless, isolated V8 environment. The connection is ephemeral, meaning no contact details or proposal contents persist in the proxy layer.

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