🚀 MCP Document Analytics Server
An MCP-powered server that allows clients to interact with APIs, parse documents, and generate intelligent analytics using LLMs.
📌 Overview
MCP Document Analytics Server is an implementation of the Model Context Protocol (MCP) that enables external clients, agents, or applications to:
📡 Send documents or payloads to an API
📄 Automatically parse and structure the document data
🤖 Run analytics using a Large Language Model (LLM)
📊 Return meaningful insights, summaries, and structured outputs
The system acts as a unified orchestration layer between:
Client applications
Document parsers
LLM engines
Analytics pipelines
This allows consumers to build intelligent workflows without managing individual integrations.
✨ Key Features
🔗 MCP-compliant tool interface
📥 API-based document ingestion
📄 Intelligent document parsing and normalization
🧠 LLM-powered analytics and insights generation
📊 Structured output (JSON-ready for dashboards and automation)
⚡ Scalable and stateless design
🧩 Pluggable parsers and LLM providers
🧪 Test-ready architecture
🏗️ Architecture Client / Agent │ ▼ MCP Server (API Layer) │ ┌────┼──────────────┐ │ │ │ ▼ ▼ ▼ Parser Engine Analytics Engine LLM Gateway (PDF, Text, (Rules + AI) (OpenAI / Local LLM) Docs, etc.)
🚀 How It Works
Client sends a document or payload to the MCP API.
Server validates and parses the document.
Parsed content is normalized into structured data.
The structured data is passed to the LLM for analytics.
The system returns insights such as:
Summaries
Key entities
Metrics
Trends
Classification
Risk flags (optional)