Franchimp MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Franchimp 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 Franchimp. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Franchimp?"
)
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 Franchimp MCP Server
Connect your Franchimp account to any AI agent to automate your franchise market research and B2B lead generation through the Model Context Protocol (MCP). Franchimp provides access to an extensive database of franchisors and franchisees, including financial requirements, investment ranges, and contact details for over 450,000+ units. This MCP server enables you to retrieve granular franchise metadata and oversee your data credits directly through natural conversation.
LlamaIndex agents combine Franchimp tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Franchise Discovery — Search for franchisors by name or keywords and fetch detailed metadata including status and investment range.
- Lead Generation — Access and list franchisee contact information, including emails and phone numbers, to fuel your outreach sequences.
- FDD Metadata — List and retrieve metadata for Franchise Disclosure Documents (FDDs) to understand legal and operational structures.
- Multi-Unit Insights — Identify and list multi-unit franchisors managing several units across different brands.
- Credit Management — Monitor your account status and remaining document download credits directly from your chat interface.
- Intelligence Research — Fetch financial stats and investment requirements to benchmark different franchise opportunities.
- Real-time Monitoring — Search for specific franchisees by email to verify records or enrich your internal CRM data.
The Franchimp MCP Server exposes 12 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 Franchimp to LlamaIndex via MCP
Follow these steps to integrate the Franchimp 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 12 tools from Franchimp
Why Use LlamaIndex with the Franchimp MCP Server
LlamaIndex provides unique advantages when paired with Franchimp through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Franchimp tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Franchimp tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Franchimp, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Franchimp tools were called, what data was returned, and how it influenced the final answer
Franchimp + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Franchimp MCP Server delivers measurable value.
Hybrid search: combine Franchimp real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Franchimp 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 Franchimp for fresh data
Analytical workflows: chain Franchimp queries with LlamaIndex's data connectors to build multi-source analytical reports
Franchimp MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Franchimp to LlamaIndex via MCP:
find_franchisee_by_email
Search franchisee by email
get_account_info
Get account attributes
get_fdd_metadata
Get FDD information
get_franchise_details
Get franchisor metadata
get_franchisee_details
Get franchisee contact info
get_investment_stats
Get investment data
list_available_credits
Check document credits
list_fdd_documents
List disclosure documents
list_franchisees
List specific franchisees
list_franchises
List all franchisors
list_multi_unit_operators
List multi-unit franchisors
search_franchisors
Search franchisor database
Example Prompts for Franchimp in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Franchimp immediately.
"List all franchisors in the database and their investment status."
"Search for franchisees with the email 'john.owner@example.com'."
"Show me the investment stats for '7-Eleven'."
Troubleshooting Franchimp MCP Server with LlamaIndex
Common issues when connecting Franchimp to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFranchimp + LlamaIndex FAQ
Common questions about integrating Franchimp 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 Franchimp 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 Franchimp to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.