"Hybrid Memory Models Combining Relational, Graph, and RAG Approaches" matching MCP servers:

Enables sending one identical brief to multiple LLMs in parallel and returning every answer verbatim, unmerged, unranked, and unsynthesized.

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

Local, searchable project memory for AI coding agents. Markdown source of truth, MCP interface, safe structured updates

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

MCP server for Parks on the Air (POTA) providing live activator spots, park details, activator/hunter stats, and scheduled activations through any MCP-compatible AI assistant.

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.

Governed cross-agent memory for coding agents with hybrid retrieval, provenance tracking, and cross-machine sync.

Enables Claude Desktop and compatible agents to search, read, add, update, and delete a locally stored, user-curated memory using hybrid retrieval with reranking and Qdrant. All processing runs locally without cloud services or API keys.

An MCP server for HF radio propagation analytics using the IONIS dataset collection, enabling natural language queries about band conditions, propagation paths, and solar correlations.

Provides persistent memory with semantic search for MCP-based AI agents, enabling them to store and recall information across sessions using vector embeddings.

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

An MCP server for tracking student learning via a knowledge graph, with spaced repetition scheduling and intelligent queries to identify gaps, misconceptions, and optimal next steps.

Provides LLM clients with a persistent, scalable knowledge graph memory system that supports semantic retrieval, contextual recall, and temporal awareness.

Enables analysis of Karate framework feature files, extracting dependencies and generating interactive dependency graphs.

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.

An MCP server that gives AI models a persistent notebook backed by a folder of Markdown files, with tools to discover, read, write, edit, and delete notes.

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.

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

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.