"Exploring RAG through defined workspaces" matching MCP servers:

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

Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.

"primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨

Provides RAG tools with local vector retrieval and web fallback using Firecrawl, enabling document ingestion and querying through MCP stdio transport.

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

A local MCP server that enables LLMs to securely search and read files within designated Google Drive folders. Supports Google Docs, Google Sheets, PDFs, and plain text with strict folder-scoping via service account authentication.

Serves UltraRAG memory to agents over stdio MCP, providing project-local and per-user global memory. It lets agents read and append standing memory and daily dialogue rounds in UltraRAG's format, with an optional browser view.

Searches local markdown files using TF-IDF retrieval and serves full documents as resources.

Enables natural-language and keyword search across Obsidian notes, returning reranked passages with provenance, and supports reading notes and incremental indexing.

Enables asking natural language questions about local videos, using Whisper transcription, ChromaDB vector storage, and Groq for timestamped answers via MCP.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

Full-stack PDF intelligence MCP server for extracting, manipulating, annotating, converting, validating, and RAG-searching PDFs through a unified tool surface and React workbench.

Enables running SQL queries, exploring metadata, and interacting with Teradata databases through the Model Context Protocol.

A local MCP server that routes QA reviews through deterministic profiles and risk-based escalation while keeping source evidence and final decisions with the host.

Unified MCP server for Polish legal data, enabling search and retrieval across case law, legislation, company register, tax rulings, public procurement, and EU sources through four aggregated tools.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Turns team chat (Slack, Discord, MS Teams, Mattermost) into a living knowledge base - a typed knowledge graph plus auto-generated wiki - exposed to AI agents through a 28-tool MCP server with semantic search, expert finding, and decision tracing.

Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.

Provides vision capabilities to text-only LLMs by acting as a cloud vision adapter layer, enabling image understanding and OCR text extraction through a single MCP tool.

A universal MCP aggregator toolkit that connects AI agents to multiple MCP servers through a single unified configuration. Features ready-made templates, cross-repo prompt workflows, and an npm package for zero-config installation.