Pricefx 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 Pricefx 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 Pricefx. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Pricefx?"
)
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 Pricefx MCP Server
Harness the power of Pricefx, the premier Cloud Pricing Optimization platform, by coupling it directly to your LLM agents. Empower your AI to navigate vast B2B catalogs, securely read customer pricing grids, and orchestrate automated Quote generation (CPQ) instantaneously via natural language prompts.
LlamaIndex agents combine Pricefx 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
- Live Catalog & Pricing — Search deep into the
fetch_productslogic to find base SKUs, and evaluate their explicit Price Math limits viaget_product - CRM & Account Rules — Query your partition tracing active CRM records via
fetch_customers, or force new structures dynamically (create_customer) - Quote Engine (CPQ) — Ask the AI to build dynamic Quotes on the fly (
create_quote) calculating complex arrays, or trace why an exist Quote ID failed approval (get_quote) - Seamless Deletion — Obliterate drafted quotes matching strict constraints from your Partition without accessing the Gateway (
delete_quote)
The Pricefx 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 Pricefx to LlamaIndex via MCP
Follow these steps to integrate the Pricefx 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 Pricefx
Why Use LlamaIndex with the Pricefx MCP Server
LlamaIndex provides unique advantages when paired with Pricefx through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Pricefx tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Pricefx tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Pricefx, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Pricefx tools were called, what data was returned, and how it influenced the final answer
Pricefx + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Pricefx MCP Server delivers measurable value.
Hybrid search: combine Pricefx real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Pricefx 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 Pricefx for fresh data
Analytical workflows: chain Pricefx queries with LlamaIndex's data connectors to build multi-source analytical reports
Pricefx MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Pricefx to LlamaIndex via MCP:
create_customer
Ensure JSON format is robust. Provision a highly-available JSON Payload generating hard Customer bindings
create_quote
Retrieve the exact structural matching verifying CPQ Generation
delete_quote
Irreversibly vaporize explicit validations extracting rich Churn flags
fetch_customers
Identify bounded CRM records inside the Headless Pricefx Platform
fetch_products
Enumerate explicitly attached structured rules exporting active pricing Catalog
fetch_quotes
Identify precise active arrays spanning native Gateway auth
get_customer
Perform structural extraction of properties driving active Account logic
get_product
Retrieve explicit Cloud logging tracing explicit Product limits
get_quote
Dispatch an automated validation check routing explicit Quote history
update_customer
Provide bulk bounds strictly formatted. Inspect deep internal arrays mitigating specific Plan Math
Example Prompts for Pricefx in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Pricefx immediately.
"Can you fetch all our active Quotes and find any that are still in Draft status?"
"We need to create a new customer record manually. Give me the JSON for a generic B2B profile named `Acme Corp`."
"Look up product ID 'MX-Mouse-001'. Tell me its base price bracket before discounts."
Troubleshooting Pricefx MCP Server with LlamaIndex
Common issues when connecting Pricefx to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPricefx + LlamaIndex FAQ
Common questions about integrating Pricefx 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 Pricefx 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 Pricefx to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.