DocSumo MCP. Extract structured data from invoices and IDs.
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DocSumo. Automate document data extraction, audit processed files, and manage IDP pipelines. Connect your AI agent to DocSumo to pull structured data from invoices, bank statements, and IDs.
Check document status, identify low-confidence reads, or audit recent results—all through natural language conversation.
What your AI agents can do
Get docsumo account metadata
Gets usage limits and metadata for your DocSumo account.
Get document extraction data
Pulls the structured data that was extracted from a specific document.
List docsumo document types
Lists all document types (like invoices or bank statements) configured in DocSumo.
Retrieves basic account information and usage limits for your DocSumo account.
Pulls the structured data extracted from a single, identified document.
Retrieves a list of all document types (e.g., invoices, bank statements) set up in your DocSumo account.
Identifies documents that failed extraction or have low confidence scores and require manual human review.
Provides a feed of the most recently processed documents across all categories.
Retrieves a list of every document processed, optionally filtering by its document type.
Identifies documents that have completed the processing workflow and passed verification.
Ask AI about this MCP
Supported MCP Clients
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019d7587get docsumo account metadata
Gets usage limits and metadata for your DocSumo account.
019d7587get document extraction data
Pulls the structured data that was extracted from a specific document.
019d7587list docsumo document types
Lists all document types (like invoices or bank statements) configured in DocSumo.
019d7587list documents awaiting review
Finds documents that need a person to check them because the extraction score was low.
019d7587list failed doc extractions
Identifies documents that failed the extraction process completely.
019d7587list latest extraction results
Shows the most recently processed documents from all types.
019d7587list processed documents
Lists all documents DocSumo has handled, letting you filter by document type.
019d7587list successfully parsed docs
Lists documents that finished processing and passed all verification steps.
019d7587quick idp health audit
Gets a high-level summary of how well the document processing is working.
019d7587search documents by filename
Searches for processed documents using a keyword found in the file name.
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Build Your Own
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What you can do with this MCP connector
Yo, this DocSumo MCP Server lets your AI client pull structured data from documents like invoices, bank statements, and IDs. You can use it to check on your whole IDP pipeline and pull data from specific files using natural language.
get_docsumo_account_metadata lets you grab your usage limits and basic account info. list_docsumo_document_types shows you every document type—like invoices or bank statements—you've got set up. get_document_extraction_data pulls the actual structured data from a specific document. list_latest_extraction_results gives you a feed of the most recently processed documents, no matter the type. list_processed_documents lists every document DocSumo has handled, and you can filter that list by document type. list_successfully_parsed_docs only shows documents that finished processing and passed all checks. list_documents_awaiting_review pinpoints documents that need a person to check 'em because the extraction score was low. list_failed_doc_extractions finds documents that totally failed the extraction process. quick_idp_health_audit gives you a high-level summary of how well the whole document processing thing is working.
You can also search_documents_by_filename by using a keyword found in the file name to find a processed document.
How DocSumo MCP Works
- 1 Connect the DocSumo integration to your AI client.
- 2 Authorize the connection using your DocSumo API Key.
- 3 Tell your agent what data you need (e.g., 'Show me all failed invoices from last week').
The bottom line is that your agent handles the API calls; you just talk to it.
Who Is DocSumo MCP For?
Finance teams that need to process large volumes of invoices and receipts. Compliance officers who must audit ID cards and bank statements for verification status. Operations leads monitoring document processing health and failure rates.
Uses the server to quickly pull structured data from invoices and receipts for bookkeeping and ledger entry.
Audits processed ID cards and bank statements to check for verification status and compliance adherence.
Monitors the overall document processing health, success rates, and bottlenecks across the organization's document pipeline.
What Changes When You Connect
- Access structured data instantly. Instead of opening a PDF and manually typing out the invoice number, use
get_document_extraction_datato pull the exact Invoice Number and Grand Total into your chat. - Manage document quality. If a document is blurry or the data is messy, your agent finds it using
list_documents_awaiting_review, telling you exactly what needs human eyes. - Audit your pipeline history. Need to know what happened last week?
list_latest_extraction_resultsgives you a chronological feed of every document that passed through the system. - Pinpoint failures fast. If a job breaks, don't waste time digging through logs. Run
list_failed_doc_extractionsto see the exact documents that failed extraction. - Monitor overall health. Use
quick_idp_health_auditto get a quick summary of processing success rates across all document types, without running ten separate reports. - Control the workflow. Use
list_docsumo_document_typesto see exactly what kind of documents (like 'utility bill' or 'passport') your system is configured to read.
Real-World Use Cases
Reconciling a batch of bank statements
The bookkeeper needs to reconcile 50 bank statements. Instead of opening each PDF and manually pulling transaction dates and amounts, they ask their agent to run list_processed_documents for 'bank statements'. The agent returns the list, and the bookkeeper then uses get_document_extraction_data on the specific files needed for the current month's entries.
Checking compliance status for new hires
The compliance officer needs to verify 10 new hires' IDs and bank statements. They prompt the agent to run list_documents_awaiting_review and list_successfully_parsed_docs. The agent filters the results, allowing the officer to instantly confirm that all required documents passed verification and are ready for the next stage.
Investigating a data loss incident
The operations manager suspects a data leak. They ask the agent to run list_failed_doc_extractions and list_latest_extraction_results. The agent shows the manager not only which files failed, but also the timestamps and types, helping pinpoint when the process broke.
Finding a specific client invoice
A user needs the data for an invoice from 'Client XYZ' from last quarter. They ask the agent to run search_documents_by_filename with the client name. The agent finds the file, and the user then uses get_document_extraction_data to pull the specific total and line items they need.
The Tradeoffs
Treating the server like a database search
Running a massive, general query across all document types to find one piece of data. This is slow, hits rate limits, and doesn't respect document state.
→
First, use list_processed_documents to narrow the scope by document type. Then, use search_documents_by_filename for the file. Finally, use get_document_extraction_data to pull the data. Don't try to do it all in one shot.
Ignoring document confidence scores
Assuming that every document that was processed is 100% accurate, and manually entering data because the extraction looks 'close enough'.
→
Always check list_documents_awaiting_review first. If documents are showing up there, don't trust the data; send them to a human for manual verification before trusting the results.
Relying on manual file naming
Searching for a document by remembering its exact file name, which changes frequently or is incomplete.
→
Use list_latest_extraction_results to see what was processed recently, or use list_processed_documents to filter by date range and document type, bypassing the need for a perfect filename.
When It Fits, When It Doesn't
Use this if you need to automate the full cycle of document data management: identifying, extracting, auditing, and verifying data from complex files like invoices or IDs. You're building a data pipeline where the document's state matters. You'll use tools like list_failed_doc_extractions to find breaks, and get_document_extraction_data to get the clean output. Don't use this if you just need to search for a file's metadata (e.g., file size or upload date); use a standard cloud storage listing tool instead. If you only need to list document types, list_docsumo_document_types is enough. This server is for deep, structured data work, not simple file retrieval.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DocSumo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking documents and data integrity shouldn't involve jumping between five different internal dashboards.
Right now, finding out if a document was processed correctly means jumping from the main document repository to the IDP dashboard. You check the file, then you check the processing status tab, then you check the audit log, and finally, you open a separate spreadsheet to manually pull the extracted totals. It's a full session of copy-pasting and cross-referencing.
With DocSumo MCP, you tell your agent the goal: 'Find the grand total for the last invoice.' The agent runs the necessary checks—from finding the file (`search_documents_by_filename`) to pulling the structured data (`get_document_extraction_data`)—and gives you the final number in one chat response. No more switching tabs.
DocSumo MCP Server: Get structured data from documents.
Manual data extraction involves opening a bank statement, finding the relevant field (like 'Total Withdrawal'), and typing it into a ledger. You have to visually confirm the data and remember which field it was.
Now, your agent handles that. You ask it to extract data from a document, and it returns the field name and the value, complete with a confidence score. You get the machine-readable data directly, not a picture of text.
Common Questions About DocSumo MCP
How do I use the `list_processed_documents` tool with a date filter? +
You tell your agent you need a filter. The agent runs list_processed_documents and takes the date/type parameters you provide in the prompt. You don't call the tool directly; you ask your agent to do it.
What is the difference between `list_processed_documents` and `list_successfully_parsed_docs`? +
list_processed_documents lists everything DocSumo has touched. list_successfully_parsed_docs only shows documents that passed all checks and are verified.
Does `get_document_extraction_data` work on any file? +
No. This tool only works on documents that have already been processed and passed through the DocSumo pipeline. You must reference a specific document ID.
How do I find documents that need human review using the DocSumo MCP Server? +
You ask the agent to run list_documents_awaiting_review. This tool specifically targets documents with low confidence scores, directing your attention to the files that need human eyes.
Can I get the account usage limits using `get_docsumo_account_metadata`? +
Yes. Running get_docsumo_account_metadata pulls the metadata and usage limits for your DocSumo account into the chat.
When should I use `list_failed_doc_extractions` versus `list_documents_awaiting_review`? +
Use list_failed_doc_extractions when a document outright fails processing. This tool identifies files that hit a hard error, like a corrupt scan. Use list_documents_awaiting_review when the document processed but the AI confidence score is too low for automation.
How does the `get_document_extraction_data` tool handle table data? +
The tool retrieves structured data, including complex table layouts. It doesn't just give you text; it gives you the row and column structure, making the data ready for use in databases or spreadsheets.
What information does `get_docsumo_account_metadata` provide besides usage limits? +
This tool gives you full metadata about your DocSumo account. You'll get things like your API key status, billing tier, and specific platform feature availability, all in one call.
How do I get a DocSumo API Key? +
Log in to your DocSumo account, navigate to the API section in your settings, and you can retrieve your unique API Key from there. API access is typically enabled for most plans.
What happens if extraction confidence is low? +
DocSumo flags documents with low confidence for manual review. You can use the list_documents_awaiting_review tool to identify these documents directly via the agent.
Does the integration support custom document types? +
Yes, as long as you have configured the document types in your DocSumo account, the agent can list them and retrieve extracted data for any of them.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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