MCP Academic RAG Server Documentation

Welcome to the comprehensive documentation for the MCP Academic RAG Server - a system for academic document processing and retrieval-augmented generation.

API Reference

Project Overview

The MCP Academic RAG Server is an enterprise-grade system that combines:

  • Document Processing: Advanced OCR, text extraction, and preprocessing

  • Vector Storage: High-performance vector databases for semantic search

  • RAG Pipeline: Retrieval-augmented generation with multiple LLM providers

  • MCP Protocol: Native integration with AI assistants like Claude

  • Monitoring: Comprehensive observability and performance tracking

  • Configuration: Enterprise-level configuration management

Key Features

📄 Multi-Format Support

Process PDF, DOCX, TXT, and other academic document formats

🔍 Advanced Search

Semantic vector search with metadata filtering and hybrid retrieval

🤖 LLM Integration

Support for OpenAI, Anthropic, Google, and custom LLM providers

⚡ High Performance

Optimized async processing with caching and batch operations

🔧 Enterprise Ready

Configuration management, monitoring, alerting, and security

🧩 Extensible

Plugin architecture for custom processors and integrations

Quick Start

  1. Installation:

    pip install mcp-academic-rag-server
    
  2. Configuration:

    cp config/config.json.example config/config.json
    # Edit configuration with your API keys
    
  3. Start Server:

    mcp-academic-rag-server --help
    mcp-academic-rag-server
    
  4. Discover and call tools:

    Connect an MCP client over stdio. See Maintained entry and verification for the isolated client handshake and MCP Tools Reference Guide for tool arguments.

Architecture Highlights

The system implements a layered, modular architecture designed for:

  • Scalability: Horizontal scaling with load balancing

  • Reliability: Comprehensive error handling and monitoring

  • Maintainability: Clean interfaces and separation of concerns

  • Performance: Async processing and intelligent caching

  • Security: Authentication, authorization, and data protection

Core Components:

See MCP Academic RAG Server - Architecture Overview for the existing architecture diagrams.

Support and Community

  • Documentation: Complete API reference and guides

  • GitHub: Source code and issues

  • Community: Developer forums and discussions

  • Enterprise: Professional support and consulting available

API Reference

core

Core Module for MCP Academic RAG Server

connectors

External service connectors for MCP Academic RAG Server

document_stores

Document Stores Package

rag

RAG (Retrieval-Augmented Generation) components for MCP Academic RAG Server

servers

Indices and Tables