"AMD" matching MCP servers:

An MCP server for AI-driven hybrid search over Xilinx/AMD FPGA documentation, enabling assistants to retrieve datasheets, user guides, and application notes through tools like search_docs.

stdio server to read markdown with images or index markdown headings from a file, folder or URL

MCP server that gives AI agents human-like persistent memory, with auto-encoding, proactive recall, and memory rooms for cross-agent context.

A high-performance MCP server providing long-term memory storage with semantic and keyword search capabilities, using SQLite and fastembed for sub-200ms queries.

A local MCP server enabling hybrid search over documents, memory, and knowledge graphs for retrieval-augmented generation, with tools for SQLite, semantic memory, and entity-relationship queries.

A high-performance MCP server providing long-term memory storage with semantic and keyword search, along with a structured agenda engine for task management.

Facilitates integration of Brave Search functionalities with AI assistants through the Model Context Protocol, enabling web and local searches using the Brave Search API.

A Model Context Protocol server that enables web search capabilities using the Tavily API, allowing AI models to retrieve current information from the internet through natural language commands.

An encrypted, local-first memory server for AI agents that uses SQLite + FTS5 hybrid search, keeping memory off the GPU to maximize HBM for inference.

MCP server that provides semantic search, graph query, and keyword search tools for interacting with DocSmith's knowledge graph and documentation.

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.

Provides hybrid search over local markdown knowledge bases using BM25 keyword search and vector semantic search. Enables indexing, querying, and retrieving markdown documentation with dual-mode support for local and remote agents.

Provides real-time, up-to-date documentation for major LLM providers (OpenAI, Anthropic, Google Gemini) to prevent hallucinations and outdated code patterns in AI agents.

A Streamable HTTP MCP server that packages QMD search and document retrieval with bounded index-maintenance operations, without exposing arbitrary shell execution.

Persistent memory for Claude Code — a self-evolving knowledge layer that survives across sessions, grows from every conversation, and surfaces relevant context automatically.

Enables natural-language semantic search over a fully local knowledge base, keeping embeddings, storage, and retrieval on the machine.

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

Enables automatic memory retrieval and injection for AI conversations to provide continuous learning through semantic search and memory management.

Enables interaction with a TrueRAG system through a GraphQL API using the Model Context Protocol (MCP), facilitating access to policies with a Python SDK and GQL library integration.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.