Finmei 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 Finmei as an MCP tool provider through the 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 Finmei. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Finmei?"
)
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 Finmei MCP Server
Connect your Finmei account to any AI agent and automate your financial operations through the Model Context Protocol (MCP). Finmei is the ideal companion for freelancers and small businesses that need to track expenses and manage invoices without the complexity of traditional accounting software.
LlamaIndex agents combine Finmei tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through the 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
- Expense Tracking — Digitally record and list all business expenses. Fetch details or delete entries directly through natural conversation.
- Tax Management — List and manage your tax types (Tax Rates) to ensure your financial records are always accurate and compliant.
- Payment Monitoring — Keep track of all payments associated with your business. List recent payments or drill down into specific transaction details.
- Business Profiling — Access your business profile metadata to ensure your agent has the right context for generating reports or invoices.
- Global Support — Fetch supported currencies and manage international transactions with support for over 180 currencies.
- Category Organization — Organize your finances by listing and applying expense categories to your records.
The Finmei 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 Finmei to LlamaIndex via MCP
Follow these steps to integrate the Finmei 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 Finmei
Why Use LlamaIndex with the Finmei MCP Server
LlamaIndex provides unique advantages when paired with Finmei through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Finmei tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Finmei tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Finmei, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Finmei tools were called, what data was returned, and how it influenced the final answer
Finmei + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Finmei MCP Server delivers measurable value.
Hybrid search: combine Finmei real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Finmei 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 Finmei for fresh data
Analytical workflows: chain Finmei queries with LlamaIndex's data connectors to build multi-source analytical reports
Finmei MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Finmei to LlamaIndex via MCP:
create_expense
Create a new expense
delete_expense
Delete an expense
delete_payment
Delete a payment
get_expense
Get expense details
get_payment
Get payment details
get_profile
Get business profile
list_categories
List expense categories
list_currencies
List supported currencies
list_expenses
List expenses
list_payments
List payments
list_tax_types
List tax rates
update_expense
Update an expense
Example Prompts for Finmei in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Finmei immediately.
"List my 10 most recent business expenses."
"Add a new expense: 'Monthly Internet Subscription', 50 USD, for today."
"Show me all available tax rates for my account."
Troubleshooting Finmei MCP Server with LlamaIndex
Common issues when connecting Finmei to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFinmei + LlamaIndex FAQ
Common questions about integrating Finmei 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 Finmei 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 Finmei to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.