Alphamoon MCP for AI Agents. Automate data extraction from any contract or invoice.
Alphamoon MCP connects your AI agent directly to advanced document processing tools. It extracts structured data from complex documents like invoices, contracts, and forms using high-fidelity OCR. You can programmatically manage entire data pipelines, list all processed files, or retrieve raw text from scanned PDFs without manual intervention.
Give Claude and any AI agent real-world access
You can programmatically list and manage all available automation pipelines to coordinate complex data extraction tasks.
The MCP retrieves specific, structured fields from processed documents, providing high-fidelity accuracy and confidence scores for critical data points like totals or IDs.
You can pull the complete recognized text, including handwritten notes, directly from scanned files and PDFs through your agent.
It allows you to list all processed documents and check their current status to maintain a comprehensive audit trail.
Your agent verifies API connectivity and retrieves account-level metadata for instant operational reporting.
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What AI agents can do with Alphamoon MCP with 12 Tools
Use these tools to manage documents, run extraction pipelines, retrieve raw text, and monitor the status of all your automated document workflows.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Alphamoon MCPCheck Alphamoon Status
Verifies the current connection status of your Alphamoon account.
Delete Document
Removes a specific document from the system record.
Get Document
Retrieves detailed information about a given document ID.
Get Extraction Results
Fetches structured data fields that were automatically extracted from a processed...
Get Ocr Results
Retrieves the full, high-fidelity recognized text content from an uploaded document.
Get Process
Gets detailed information about a specific automated processing pipeline.
Get Template
Retrieves the configuration details for a defined data extraction template.
List Documents By Process
Lists all documents that were processed using a specific automation pipeline.
List Documents
Provides an overview and list of all managed documents in the system.
List Processes
Generates a directory listing of all available document automation pipelines you've...
List Templates
Shows the list and details of every data extraction template configured.
Upload Document
Sends a new document file to Alphamoon for processing and analysis.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Alphamoon, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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Managed infra
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Sandboxed per request
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No stored credentials
DLP Enforced
Policy on each call
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~60% cost reduction
The Pain of Document Data Entry Solved with Vinkius AI Gateway
Right now, getting critical numbers out of documents is slow and error-prone. You open a PDF, navigate to the invoice total, copy it into Excel, then repeat that process for the next 49 invoices. If you need the raw data from an old scan, you’re stuck staring at garbled text or manually transcribing handwritten notes.
With this MCP, your AI acts like a dedicated document engineer. You simply ask: 'What were the total amounts on these five PDFs?' The system handles the whole workflow—uploading, processing, extracting—and gives you clean data points instantly.
Get Structured Data with Alphamoon's Extraction Tools
You no longer have to jump between a document viewer and your database. You don't need to manually check if the data field you found is reliable; `get_extraction_results` provides confidence scores, telling you exactly how sure the system is about that number.
Your AI agent connects the dots. It handles the complexity of pipeline orchestration so you just get the final answer: structured data ready for your next workflow step.
What your AI can actually do with this
Don't spend hours manually transcribing numbers off receipts or digging through PDF logs. This MCP lets you treat document processing like a conversation with an expert engineer. Your AI client handles the heavy lifting: it processes documents via structured pipelines and pulls out exact fields—like total amounts, dates, and vendor names—with confidence scores attached.
Need to check which files ran through a specific template? You can list all processed records and monitor their status instantly. Even if you need the raw text from an old scan, your agent gets it for you. Because Vinkius hosts this MCP, you connect once to access Alphamoon's full suite of document intelligence tools right alongside everything else in the catalog.
019dd0b8-3844-71e7-a52d-9f012e75194d Here's how it actually works
The bottom line is that you tell your AI what data you need from a document, and it automatically extracts and presents it.
First, subscribe to the Alphamoon MCP and grab your unique API Key from your dashboard settings.
Next, give your AI client a command—like 'extract all invoice totals for last month'—and let it call the appropriate tool.
Finally, your agent processes the documents and returns structured data directly into your conversation, ready to use.
Who is this actually for?
This MCP is essential for anyone drowning in paper records or messy PDFs. If your job involves converting information trapped inside documents—whether those are invoices, legal contracts, or ID scans—into usable data, this is the tool you need.
They use it to automate ingesting invoice data into custom reports without ever leaving their current workspace.
They instantly verify extraction results for high-volume batches using natural language commands, knowing if the data is accurate or needs review.
They integrate high-speed document intelligence directly into custom automation workflows with simple AI queries to build better apps.
What Changes When You Connect
Stop copying fields manually. Instead, simply ask your agent to 'What is the total amount on document 90210?'. The AI will use get_extraction_results and give you a precise, structured answer with confidence scores.
Track everything without logging into a separate dashboard. Use list_documents_by_process to see every file run through your 'Invoice Processing' pipeline and check its current status instantly.
Need the full context? If extraction fails or if the document has handwritten notes, you can use get_ocr_results to pull the complete recognized text from scanned PDFs that way.
It's not just about running a file. You can manage the whole system using tools like list_processes and list_templates, ensuring your data pipelines are always correctly configured before upload.
When you need to start a new workflow, use upload_document. Your agent takes that raw file and runs it through the right process without you having to touch any other UI screens.
See it in action
Processing Batch Invoices
A Financial Analyst receives 50 PDF invoices daily. Instead of logging into a system and copying totals, they prompt their agent: 'Process these new files and give me the total amount for each.' The agent runs list_documents to track them and uses get_extraction_results to populate a spreadsheet automatically.
Auditing Contracts
An Operations Manager needs to confirm which documents were processed using the 'Client Onboarding' pipeline. They ask their agent to use list_documents_by_process, instantly generating an audit trail they can review and share.
Extracting Data from Scanned Forms
A developer gets a physical, scanned ID form that needs data captured. They upload it (upload_document), then prompt the agent to use get_ocr_results first, ensuring all raw text is available before attempting structured field extraction.
Debugging Workflows
An analyst notices a processing failure. Instead of guessing what went wrong, they ask their agent to run check_alphamoon_status and then use get_process to review the exact steps and settings for that specific pipeline.
The honest tradeoffs
What to watch out for, and the recommended way to handle each one.
Treating it like a general file reader
Just uploading a document and asking, 'What is this about?' The agent can't read the intent or structure without knowing what to look for.
Always define the task. Use your agent to run list_templates first, select the correct template (e.g., 'Invoice'), then upload the file and ask it to use get_extraction_results. This forces structured output.
Ignoring audit trails
Running a batch job and then forgetting where the files went or if they actually ran successfully.
Immediately after running any process, use list_documents to get a master list. If you need to check a specific pipeline's output, run list_documents_by_process.
Assuming raw text is enough
Getting the raw OCR data and trying to manually find the total amount among paragraphs of garbage text.
First use get_extraction_results. This filters out all noise and gives you clean, structured values like 'Total Amount: $123.45' instantly.
When It Fits, When It Doesn't
Use this MCP if your core problem is turning unstructured or semi-structured documents into reliable, usable data points (e.g., invoices, contracts, receipts). You need the fidelity of OCR and the reliability of predefined pipelines. Don't use it if you just need general file storage—use a simple cloud drive service instead. Also, don't use it if your goal is summarizing knowledge from multiple sources; for that, connecting an MCP to a specialized Retrieval-Augmented Generation (RAG) catalog is better. However, if the data source is always a document, Alphamoon provides the deep extraction capabilities you need.
Questions you might have
How do I start using Alphamoon with my current AI client? +
You subscribe to this MCP on Vinkius, grab your API Key from the Alphamoon dashboard, and then give your agent a natural language command.
Can Alphamoon handle handwritten notes in documents? +
Yes. By calling get_ocr_results, you access the complete recognized text, including any detected handwriting or marginalia from scanned files.
What is a 'pipeline' and why do I need to list them? +
A pipeline defines a structured workflow (e.g., OCR -> Extract -> Validate). Using list_processes lets you see all available pipelines so you know which one fits your specific document type.
If I upload 100 invoices, how do I get the totals? +
Upload them using upload_document. Then, prompt your agent to use list_documents_by_process and request structured data using get_extraction_results.
Is Alphamoon just for PDFs? +
No. It handles various file types, including scanned images and complex forms, because of its high-fidelity OCR capability.