"Land Rover" matching MCP servers:

Provides a single tool to query a knowledge base of the Land Rover Discovery II maintenance manual, using RAG with LLAMA 3 and ChromaDB.

Enables MCP clients to screen lab results against published criteria with deterministic Python, search Australian contaminated-land guidance with cited passages, and draft guarded results sections whose numbers and citations are validated. All four tools are read-only and keep figures and citations under code control for a qualified person to check.

Enables MCP clients like Claude Code or Codex to propose edits to documents and databases, with changes appearing as suggestions that people accept or reject before they land.

Provides persistent, cross-session memory for AI agents, letting them store, search, and manage memories with tools like remember, recall, forget, list, summarize, and import/export.

Enables local semantic and full-text search over Markdown notes through MCP, returning relevant passages ranked by meaning and exact terms without requiring a GPU or hosted APIs.

Provides tools for semantic decomposition, proof search, knowledge graph operations, and neuro-symbolic reasoning that bridges neural LLMs with symbolic AI through RDF triples, lambda calculus, and compositional intelligence principles.

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.

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

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

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.