Bidsketch MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Create Client, Create Proposal, Get Proposal Details, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Bidsketch 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 App Connector for LlamaIndex
The Bidsketch app connector for LlamaIndex is a standout in the Document Management category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Bidsketch. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Bidsketch?"
)
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 Bidsketch MCP Server
Connect your Bidsketch account to any AI agent and take full control of your professional sales proposals and client management workflows through natural conversation.
LlamaIndex agents combine Bidsketch tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Proposal Orchestration — List and manage all sales proposals programmatically, retrieving detailed status, high-fidelity values, and associated client metadata in real-time
- Client Relationship Management — Programmatically create and manage your directory of prospects and organizations to maintain a perfectly coordinated sales database
- Template Intelligence — Access and monitor your library of proposal templates to ensure your high-fidelity brand styling and content are consistently applied
- Deal Tracking Architecture — Retrieve granular details for specific proposals, including pricing components and high-fidelity descriptions directly through your agent
- Sales Visibility Monitoring — Access comprehensive overviews of your active proposal pipeline and client growth to coordinate your revenue operations efficiently
The Bidsketch MCP Server exposes 6 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.
All 6 Bidsketch tools available for LlamaIndex
When LlamaIndex connects to Bidsketch through Vinkius, your AI agent gets direct access to every tool listed below — spanning proposal-management, contract-automation, sales-cycle, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new client
Pass data as a JSON string. Create a new proposal
Get specific proposal details
List all clients
List all sales proposals
List all proposal templates
Connect Bidsketch to LlamaIndex via MCP
Follow these steps to wire Bidsketch into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Bidsketch MCP Server
LlamaIndex provides unique advantages when paired with Bidsketch through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Bidsketch tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Bidsketch tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Bidsketch, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Bidsketch tools were called, what data was returned, and how it influenced the final answer
Bidsketch + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Bidsketch MCP Server delivers measurable value.
Hybrid search: combine Bidsketch real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Bidsketch 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 Bidsketch for fresh data
Analytical workflows: chain Bidsketch queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Bidsketch in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Bidsketch immediately.
"List all my active sales proposals in Bidsketch."
"Create a new client 'John Doe' (john@example.com) for 'Acme Corp'."
"Show the status and value for proposal ID 'prop_123'."
Troubleshooting Bidsketch MCP Server with LlamaIndex
Common issues when connecting Bidsketch to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBidsketch + LlamaIndex FAQ
Common questions about integrating Bidsketch MCP Server with LlamaIndex.