"Automated PDF Processing Server with AI Workflow and Payment Integration" matching MCP servers:

Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.

Enables AI assistants to use Neo4j knowledge graphs and Qdrant vector databases for hybrid reasoning, combining structured facts with semantic search for advanced knowledge management, research analysis, and standardized coding workflows.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

A Model Context Protocol server that enables AI agents to read, search, and extract content from PDF files.

Enables AI assistants to query PDF documents by ingesting them into a vector database and generating answers grounded in the actual documents.

A local-first MCP server that ingests PDFs, extracts structure, and provides semantic search and sequential navigation tools for AI clients to query and learn from documents.

A local RAG MCP server for PDF development experience, enabling document ingestion, semantic search, and Q\&A with source citations using TF-IDF and cosine similarity.

This MCP server enables AI agents to view PDFs as accessible HTML with bounding-box citations, and provides tools for layout-aware parsing, schema extraction, cross-document Q&A, and PDF rendering.

Production-ready MCP server that integrates OpenAI API with extensible tool support, enabling dynamic plugin loading and knowledge search capabilities through multiple interfaces including CLI and browser UI.

A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.

Enables chat with multiple LLM providers (OpenAI and Anthropic) while maintaining persistent conversation memory. Provides extensible tool framework for various operations including echo functionality and conversation storage/retrieval.

MCP server for NodeBB forums that enables AI assistants to access forum data, search topics, and perform semantic search via the Model Context Protocol.

Enables AI agents to download, index, and semantically search PDF research papers using 8 MCP tools.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

A document knowledge base system that enables users to upload PDFs and query them semantically through a web interface or via the Model Context Protocol, allowing integration with AI tools like Cursor.

Enables agents to extract clean structured JSON tables from any PDF with per-cell citations to the source page.

Implements a Model Control Protocol server integrated with Google Gemini LLM, providing a flexible framework for building AI-powered applications.

Enables intelligent ingestion and querying of PDF, Markdown, and text files using hybrid search that combines keyword matching and semantic embeddings with citations.

Enables a persistent local library for mathematical PDFs with cached LaTeX extraction, full-text search in English and Greek, and page/image retrieval over MCP.

Enables RAG over messy PDFs — extract, chunk, embed, and search scanned, multi-column, and table-heavy documents.