Alphamoon MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Alphamoon Status, Delete Document, Get Document, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Alphamoon 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 App Connector for LlamaIndex
The Alphamoon app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Alphamoon. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Alphamoon?"
)
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 Alphamoon MCP Server
Connect your Alphamoon account to any AI agent and take full control of your automated document processing and intelligent data extraction workflows through natural conversation.
LlamaIndex agents combine Alphamoon 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
- Pipeline Orchestration — List and manage available document automation pipelines programmatically to coordinate high-fidelity data extraction tasks
- AI Data Extraction — Programmatically retrieve structured fields from processed documents (invoices, IDs, etc.) with high-fidelity accuracy and confidence scores
- Raw OCR Intelligence — Access the complete high-fidelity recognized text (OCR) from scanned files and PDFs directly through your agent
- Document Lifecycle Management — List all processed documents and monitor their status programmatically to maintain a perfectly coordinated audit trail
- Infrastructure Monitoring — Verify API connectivity and retrieve account-level metadata directly through your agent for instant operational reporting
The Alphamoon 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.
All 12 Alphamoon tools available for LlamaIndex
When LlamaIndex connects to Alphamoon through Vinkius, your AI agent gets direct access to every tool listed below — spanning alphamoon, ocr-api, document-extraction, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Delete a document
Get document details
Get extraction results
Get OCR results
Get process details
Get template details
List documents
List documents by process
List processes
List templates
Upload a document
Connect Alphamoon to LlamaIndex via MCP
Follow these steps to wire Alphamoon into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Alphamoon MCP Server
LlamaIndex provides unique advantages when paired with Alphamoon through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Alphamoon tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Alphamoon tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Alphamoon, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Alphamoon tools were called, what data was returned, and how it influenced the final answer
Alphamoon + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Alphamoon MCP Server delivers measurable value.
Hybrid search: combine Alphamoon real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Alphamoon 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 Alphamoon for fresh data
Analytical workflows: chain Alphamoon queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Alphamoon in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Alphamoon immediately.
"List all my document automation pipelines in Alphamoon."
"Show the extraction results for document ID '90210'."
"Get the raw OCR text from document '90210'."
Troubleshooting Alphamoon MCP Server with LlamaIndex
Common issues when connecting Alphamoon to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAlphamoon + LlamaIndex FAQ
Common questions about integrating Alphamoon MCP Server with LlamaIndex.