10x fewer tokens.
Same document intelligence.
MCP Servers that turn ECM repositories into structured knowledge — without mass ingestion.
Mass ingestion is the wrong answer.
Every major AI platform tells you the same thing: ingest all your documents, build a vector index, and retrieve context via similarity search. It sounds elegant. In practice, it creates a different set of problems.
When you push tens of thousands of documents into a RAG pipeline, you're making a bet. You're betting that the chunking strategy will preserve the meaning of complex multi-page contracts. You're betting that the embeddings will surface the right clause when an agent asks a nuanced compliance question. Most of the time, the system gives you something plausible — and that's the dangerous part.
DocDigitizer MCP Servers take a different approach. Instead of ingesting everything upfront and hoping retrieval works, we expose your document repository as a structured MCP endpoint. AI agents query for what they need, when they need it, receiving pre-processed structured data — not raw text chunks. The result: 10x fewer tokens consumed, accurate extraction on the first try, and full preservation of your ECM's metadata model.
Two architectures. One clear winner.
Compare how traditional RAG handles your ECM versus the DocDigitizer MCP Server approach.
How It Works
Four steps from ECM connection to production-ready AI agent.
Connect
Point the MCP Server at your ECM. Provide read credentials, define the repository scope. No document migration required.
Pre-process
DocDigitizer extracts structured data from documents on first access. Results are cached with TTL. Multi-page, multi-format handled automatically.
Query
Your AI agent sends semantic queries via MCP protocol. The server returns structured JSON fields — not raw text chunks.
Scale
Incremental sync keeps the cache fresh. Add repositories, expand document types, deploy additional agent workloads without reindexing.
Key Capabilities
Built specifically for enterprise document repositories, not retrofitted from a general-purpose RAG framework.
Intelligent Pre-Processing
Documents are extracted to structured JSON on first access using DocDigitizer's 371+ type extraction engine. Tables, signatures, line items, and metadata are all preserved.
Smart Caching
Extracted results are cached with configurable TTL. Unchanged documents are never re-extracted. Cache warm-up runs in the background without blocking agent queries.
Token Optimization
Instead of returning raw document text, the MCP Server returns only the structured fields the agent requested. A 40-page contract becomes a 900-token JSON response.
Incremental Sync
Monitors your ECM for changes using native change-detection APIs. New documents are processed automatically. Amended documents invalidate their cache entry and are re-extracted.
MCP Protocol Native
Exposes a fully compliant MCP server interface. Works with Claude, GPT-4, Gemini, and any agent framework that supports the Model Context Protocol specification.
Semantic Queries
Agents query using natural language or structured field paths. The server resolves queries against extracted schema — no embedding similarity threshold to tune.
Deployment Options
Cloud-hosted for fast start, on-premises proxy for data sovereignty.
☁ Cloud MCP Server
Managed infrastructure. DocDigitizer hosts the MCP Server. Your ECM credentials are stored encrypted in our EU-based vault.
- Zero infrastructure to manage
- Up and running in under 30 minutes
- Automatic updates and scaling
- EU data processing, ISO 27001 certified
- SLA: 99.9% uptime
🏠 On-Premises MCP Proxy Enterprise
Deploy the MCP Proxy inside your network perimeter. Your documents never leave your infrastructure.
- Docker or Kubernetes deployment
- No outbound document traffic
- Air-gapped environment support
- Your keys, your infrastructure
- Custom SLA and support tiers available
Supported Connectors
Native connectors for major ECM platforms. Custom connectors available via the REST bridge.
| ECM Platform | Status | Connection Method | Metadata Preservation |
|---|---|---|---|
| M-Files | Coming Soon | M-Files REST API v2 | Full — classes, properties, workflows |
| SharePoint Online | Planned | Microsoft Graph API | Full — content types, columns, permissions |
| Google Drive / Workspace | Planned | Google Drive API v3 | Partial — file metadata, labels |
| Custom ECM (REST bridge) | Available | REST API bridge | Configurable via schema mapping |
Need a connector not listed here? Contact us — custom connector development is available for enterprise customers.
Use Cases
Production deployments across regulated industries where document accuracy matters.
Enterprise Knowledge Agents
Let internal AI assistants answer questions by querying your document repositories. Accurate answers grounded in your actual policies, contracts, and procedures.
Contract Intelligence
Agents extract obligations, deadlines, counterparty data, and renewal clauses across your contract portfolio. Structured output, not free-text summaries.
Compliance Automation
Continuously monitor documents against compliance rules. MCP Server exposes regulatory filings and internal policies as structured data for automated rule-checking agents.
Customer Support
Give support agents instant access to customer contracts, SLAs, and order histories. Structured retrieval means no hallucinated terms or invented clause numbers.
Due Diligence
M&A teams run structured queries across target company document rooms. Extract financial schedules, liability clauses, and IP ownership without manual review.
Policy Q&A
HR and legal teams deploy agents that answer employee questions against the current policy library. Always sourced from the live ECM, always version-accurate.
Security & Compliance
Enterprise security built in, not bolted on.
Management
Controls
in Cloud
Processing
Pricing
Based on connected repositories, monthly document volume, and query usage.
What determines your cost
- ●Connected RepositoriesPer ECM repository connected. One M-Files vault, one SharePoint site collection, etc.
- ●Monthly Document VolumeDocuments extracted per month. Cached extractions do not count toward volume.
- ●Query VolumeMCP queries per month. High-cache workloads significantly reduce costs.
Frequently Asked Questions
How is this different from standard RAG?
Standard RAG ingests documents as raw text, generates embeddings, and retrieves approximate matches via cosine similarity. DocDigitizer MCP Servers extract structured data from documents on-demand and return precise JSON fields to agents via MCP protocol. You get deterministic, structured answers rather than approximate text retrieval — and consume 10x fewer tokens per agent session.
Does my document data leave my systems?
In Cloud mode, documents are fetched from your ECM over an encrypted connection, processed, and the resulting structured data is returned. Raw document content is not stored — only the extracted structured output is cached (with configurable TTL). In On-Premises mode, nothing leaves your network perimeter. All processing happens inside your infrastructure.
Do you support on-premises deployment?
Yes. The On-Premises MCP Proxy is available for Enterprise customers. It runs as a Docker container or Kubernetes deployment inside your network. The DocDigitizer extraction engine runs locally. Your documents never leave your infrastructure, and the MCP endpoint is exposed only to your internal agent infrastructure.
How does the system stay up to date when documents change?
The MCP Server monitors your ECM for changes using native change-detection APIs (M-Files change events, SharePoint webhooks, etc.). When a document is updated, its cached extraction is invalidated. On next query, the document is re-extracted automatically. You configure sync frequency from 5 minutes to 24 hours depending on how time-sensitive your use case is.
Which AI agent frameworks does it work with?
Any framework that supports the MCP protocol: Claude Desktop, Claude API with MCP tool support, OpenAI Agents SDK (via MCP bridge), LangChain, LlamaIndex, CrewAI, and custom agent implementations. If your framework can call an MCP server, it works with DocDigitizer MCP Servers.
What document types can be extracted?
DocDigitizer's extraction engine supports 371+ document types including invoices, contracts, purchase orders, bank statements, ID documents, technical drawings, medical records, legal filings, and custom document types defined via schema. Multi-page documents, tabular data, handwritten annotations, and scanned images are all supported.
Ready to connect your ECM to AI?
Join the early access programme. We're onboarding M-Files customers first.
Or email us at hello@docdigitizer.com