"Ram" matching MCP servers:

Caches and serves DDR/DRAM weekly price series from memorys.com and historical memory technology data, with tools for refresh, validation, analytics, forecasting, and chart rendering.

An MCP server that connects to the Ramp API, allowing users to interact with their Ramp financial data through natural language using MCP clients like Cursor or Claude Desktop.

A Model Context Protocol server that enables LLMs to interact with Ramp's financial data by retrieving, analyzing, and running tasks through Ramp's Developer API, using an in-memory SQLite database to overcome token limitations.

An MCP server that exposes AWS EC2 pricing data with an option to search by CPU, RAM, networking

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.

Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.

Give your AI agents access to 8,500+ community curated awesome lists with over 1 million curated resources.

Enables any MCP host to search and answer over your own documents with hybrid BM25+dense retrieval, cross-encoder reranking, and grounded, cited responses that refuse when no evidence is found.

A local-first MCP server that indexes code repositories and enables AI assistants to search, fetch, and navigate code using BM25 hybrid retrieval, supporting common languages and tools like Codex and ChatGPT.

Local-first agent memory & knowledge service: hybrid retrieval (vector + BM25/RRF) + memory governance (decay, dedup, freshness), REST + MCP dual protocol, fully offline without LLM. Python.

Provides semantic vector search over local codebases via MCP, enabling hybrid search (dense + sparse + RRF) for any MCP client like GitHub Copilot or Claude Desktop.

Enables AI agents to parse PDFs and search local document context through multimodal extraction and vector-based retrieval, all exposed as MCP tools.

Enables any LLM to process arbitrarily long contexts through recursive decomposition, without requiring external LLM APIs.

Provides persistent, searchable memory across AI coding agent and chat history (Claude Code, Codex, Gemini CLI, ChatGPT, and more) via retrieval-augmented generation, enabling semantic and hybrid search to retain context across sessions.

Grok asked for MCP on a URL. This is it. First MCP server built for Grok URL-based • Zero config • Just works

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.

A fully modular RAG system with MCP protocol integration, enabling hybrid retrieval, multimodal support, and dual-mode transport for connecting to AI assistants like GitHub Copilot and Claude Desktop.

RAG Vault lets your AI coding assistant search your private documents locally. Everything runs on your machine and your data stays private.

Intelligent knowledge base system that enables users to process documents in 25+ formats, perform semantic search and Q\&A through vector retrieval. Supports multiple AI models including OpenAI and DouBao with local processing capabilities.

Integrates R2R (Retrieval-Augmented Generation) with Claude Desktop, enabling semantic search across knowledge bases and RAG-based question answering with support for vector, graph, web, and document search.