Fee Navigator 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 Fee Navigator 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 Fee Navigator. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Fee Navigator?"
)
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 Fee Navigator MCP Server
Connect your Fee Navigator account to any AI agent and take full control of your merchant statement analysis and proposal workflow through natural conversation.
LlamaIndex agents combine Fee Navigator 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
- Merchant Orchestration — List all managed merchants and fetch detailed profiles including current processing metadata natively
- AI Statement Analysis — Trigger instant AI-powered analysis for uploaded merchant statements to identify hidden fees flawlessly
- Proposal Intelligence — List, inspect, and track savings proposals to optimize your sales pipeline natively
- Audit Management — Access detailed statement audits to verify processing costs and potential overcharges synchronously
- Industry Benchmarking — Retrieve real-time industry statistics and savings benchmarks to validate your offers flawlessly
- Document Flow — Manage statement uploads and tracking statuses directly from the cloud without manual portal navigation
- Identity Context — Verify your API token user profile and account information through the agent flawlessly
The Fee Navigator 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 Fee Navigator to LlamaIndex via MCP
Follow these steps to integrate the Fee Navigator 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 Fee Navigator
Why Use LlamaIndex with the Fee Navigator MCP Server
LlamaIndex provides unique advantages when paired with Fee Navigator through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Fee Navigator tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Fee Navigator tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Fee Navigator, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Fee Navigator tools were called, what data was returned, and how it influenced the final answer
Fee Navigator + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Fee Navigator MCP Server delivers measurable value.
Hybrid search: combine Fee Navigator real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Fee Navigator 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 Fee Navigator for fresh data
Analytical workflows: chain Fee Navigator queries with LlamaIndex's data connectors to build multi-source analytical reports
Fee Navigator MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Fee Navigator to LlamaIndex via MCP:
analyze_statement
Trigger AI analysis for an uploaded statement
get_account_info
Get Fee Navigator account details
get_audit
Get details for a specific audit
get_industry_stats
Get merchant service industry savings benchmarks
get_me
Get current API token identity info
get_merchant
Get details for a specific merchant
get_proposal
Get details for a specific proposal
list_audits
List all statement audits
list_merchants
List all merchants in your Fee Navigator account
list_proposals
List all savings proposals
list_recent_activities
List recent merchant analysis activities
upload_statement
Upload a merchant statement for analysis
Example Prompts for Fee Navigator in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Fee Navigator immediately.
"List all active merchants in my account."
"Show me the potential savings for proposal P-789."
"Check the current industry savings benchmarks."
Troubleshooting Fee Navigator MCP Server with LlamaIndex
Common issues when connecting Fee Navigator to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFee Navigator + LlamaIndex FAQ
Common questions about integrating Fee Navigator 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 Fee Navigator 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 Fee Navigator to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.