Appfigures MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Appfigures as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Appfigures. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Appfigures?"
)
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 Appfigures MCP Server
The Appfigures MCP Server provides your AI agent with direct access to your mobile app intelligence and store data. Gain instant insights into your app's performance across iOS, Google Play, and other major stores using simple natural language.
LlamaIndex agents combine Appfigures tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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.
Key Features
- Product Management — List and search for your apps and those of your competitors across all major app stores.
- Sales & Revenue Reporting — Get detailed reports on downloads, updates, returns, and net proceeds.
- Subscription Analytics — Monitor your subscription health, churn, and active subscriber metrics.
- Review Analysis — Retrieve and analyze user feedback to identify bugs, feature requests, and sentiment.
- Rankings & Visibility — Track your daily category and keyword rankings to optimize your ASO strategy.
- Competitive Intelligence — Search and monitor any app on the market to stay ahead of the competition.
The Appfigures MCP Server exposes 11 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 Appfigures to LlamaIndex via MCP
Follow these steps to integrate the Appfigures 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 11 tools from Appfigures
Why Use LlamaIndex with the Appfigures MCP Server
LlamaIndex provides unique advantages when paired with Appfigures through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Appfigures tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Appfigures tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Appfigures, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Appfigures tools were called, what data was returned, and how it influenced the final answer
Appfigures + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Appfigures MCP Server delivers measurable value.
Hybrid search: combine Appfigures real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Appfigures 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 Appfigures for fresh data
Analytical workflows: chain Appfigures queries with LlamaIndex's data connectors to build multi-source analytical reports
Appfigures MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Appfigures to LlamaIndex via MCP:
get_account_check
Verify Appfigures account connection
get_external_accounts
List linked store accounts
get_ranks
Get daily category and keyword rankings
get_revenue_report
Get revenue and proceeds data
get_sales_report
Get sales data (downloads, updates, returns)
get_subscriptions_report
Get subscription metrics (active, churn, etc.)
get_user_info
Retrieve authenticated user information
list_featured
Track when apps are featured on app stores
list_my_products
List all mobile apps in your Appfigures account
list_reviews
List app reviews for your products
search_products
Search for any mobile app across all supported stores
Example Prompts for Appfigures in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Appfigures immediately.
"Show me the sales report for the last 30 days."
"What are the latest reviews for my iOS app?"
"Search for the 'Instagram' app on the App Store."
Troubleshooting Appfigures MCP Server with LlamaIndex
Common issues when connecting Appfigures to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAppfigures + LlamaIndex FAQ
Common questions about integrating Appfigures 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 Appfigures 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 Appfigures to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.