How to Use the Bidsketch MCP in LlamaIndex

Q: Can LlamaIndex update Bidsketch records?

You can use createproposal to push new entries into your account. The system treats these as standard API calls while maintaining your index integrity.

Index your sales history by connecting Bidsketch to your LlamaIndex knowledge base.

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Connect Bidsketch MCP to LlamaIndex

Create your Vinkius account to connect Bidsketch 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 Bidsketch with LlamaIndex

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Index proposals with LlamaIndex

Use `get_proposal_details` to pull specific document content into your vector store. You can now perform semantic searches across your entire sales history. It turns static proposal data into a searchable asset. You stop hunting through folders and start querying your own past performance.

Search client lists via LlamaIndex

Pipe the results of `list_clients` into your index to maintain a current view of your leads. The agent sees the full list and remembers who you talked to last. This creates a map of your relationships that the AI can actually use. It makes finding the right contact details instant.

Build RAG apps with this MCP Server

Connect your proposal templates to your retrieval pipeline. When you call `list_templates`, the index updates to reflect your current sales collateral. Your RAG application stays current without manual indexing. It ensures the agent always pulls the latest version of your documents.

Setup guide

Set up Bidsketch 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 Bidsketch 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 Bidsketch tools.",
)
response = await agent.run("List recent Bidsketch 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 Bidsketch. 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.

Why Choose Vinkius

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Bidsketch MCP in LlamaIndex

Call the tools to fetch the data, then index the results into your vector store. You can then run natural language queries against your proposal history.

No, the credentials reside in the Vinkius gateway. LlamaIndex only receives the token required to execute the specific tool commands you authorize.

Your document information is encrypted during transit and resides only in your local vector index. No third party gains access to your sales records.

You can use `create_proposal` to push new entries into your account. The system treats these as standard API calls while maintaining your index integrity.

We isolate your proposal data using a zero-trust sandbox. Your information travels directly from the server to your index, bypassing public endpoints.

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