"Ram" matching MCP servers:

Provides persistent, scoped shared memory for collaborating AI agents, with tools for storing observations, semantic recall, and handoff workflows. Backed by PostgreSQL and exposed through MCP.

Enables AI assistants to perform retrieval-augmented generation with hybrid search, reranking, multi-modal image processing, and RAG evaluation through standardized MCP tools.

MCP server providing tools for entity extraction, query refinement, and relevance checking to build Agentic RAG applications.

An agentic AI system that orchestrates multiple specialized AI tools to perform business analytics and knowledge retrieval, allowing users to analyze data and access business information through natural language queries.

Implements a RAG workflow that integrates with any custom knowledge base and can be triggered directly from the Cursor IDE.

Connects a RAG application to open-webui using Model Context Protocol (MCP), enabling server-to-client communication for context retrieval and tool usage in remote environments through Server-Sent Events (SSE).

Speeds up coding agents by predicting and pre-executing upcoming tool calls, then safely returning validated cached results to eliminate wait time.

Enables browser automation for coding agents via MCP, allowing them to open pages, search, extract data, click, type, and complete multi-step tasks with fast single-round-trip decisions.

Enables goal-driven mission orchestration for Goose, turning a user goal into a structured plan with an approval gate, isolated workers in git worktrees, dual validation, auto-correction, and crash recovery to produce validated code.

Facilitates two-stage reasoning processes using DeepSeek for detailed analysis and supports multiple response models such as Claude 3.5 Sonnet and OpenRouter, maintaining conversation context and enhancing AI-driven interactions.

Enables web search for the pi coding agent using z.ai GLM native search with a DuckDuckGo fallback.

Bridges Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) applications, allowing MCP clients such as Claude Desktop to discover and invoke ACP agents as tools and resources.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

Enables autonomous agents to discover and bid on unused LLM token quota through a machine-to-machine secondary exchange protocol. It utilizes a Proof-of-Residue handshake to verify compute capacity and facilitate the real-time acquisition of verified residue tokens.

An MCP server that autonomously optimizes ONNX ML models for Arm64 deployment, providing tools to analyze models, apply real INT8 quantization, benchmark performance, and generate Arm64-optimized Docker deployment packages.

Exposes ChatATP Studio's backend API as MCP tools over Streamable HTTP, enabling clients to manage agents, knowledge bases, MCP connections, HTTP APIs, LLM providers, messaging platforms, and teams with forwarded authorization.

An open protocol server that implements Anthropic's Model Context Protocol to enable seamless integration between LLM applications and RAG data sources using Sionic AI's Storm Platform.

Enables orchestrating multi-agent AI coding workflows with Git worktree isolation, parallel testing, and security scanning via the Model Context Protocol.

Enables personalized AI tutoring by allowing students to upload PDF/DOCX study materials that are processed and indexed for semantic search. Provides intelligent responses based on the student's own learning materials using RAG technology.