"Information about medical law" matching MCP servers:

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

A multi-agent AI system that reads Indian contracts, flags unfair clauses with severity scores, and provides citations to Indian law. Runs as an MCP server in Claude Desktop.

Enables Claude Code to query and control the SuperInstance fleet, including fleet status, conservation law checks, semantic search, and agent registry.

Enables users to register and manage city entities, discover their MCP tools, and orchestrate calls to those tools while combining results into a single response.

Automatically analyzes and dispatches user tasks to appropriate handlers, supporting development task processing via Miyabi Agent and medical AI academic article generation. Provides intelligent task classification and routing for development, writing, and general tasks.

An AI-powered eldercare platform that enables AI agents to monitor passive sensors, generate personalized care plans, and access specialized healthcare knowledge bases. It provides tools for passive monitoring of senior activities, medical document OCR, and real-time alert management for caregivers.

Provides AI-powered medical image analysis tools for LLM agents, enabling tasks such as X-ray classification, interactive segmentation, and visual question answering. It supports multi-step diagnostic reasoning and clinical workflows through a suite of specialized medical AI models.

An MCP server for analyzing images using OpenRouter vision models, offering capabilities like automatic image resizing, model configuration, and handling custom queries about images.

Enables Claude to remember information about users across chats using a persistent local knowledge graph that stores entities, relationships, and observations.

An MCP-based trivia game server where AI creates rounds with two true statements and one false 'twist' about various topics, letting players guess which statement is false.

Enables Claude to remember information about users across conversations by storing and retrieving data as entities, relations, and observations in a persistent local knowledge graph.

Generates AI-powered clarifying questions for user task requests using Claude, helping gather detailed requirements about tech stack, architecture, deployment, and project scope through categorized, contextually relevant questions.

A server that enables natural-language queries about GitHub repositories and returns answers backed by live GitHub data.

Enables agents to file, decide, and escalate business exceptions only when backed by precedent that is still good law, checking authority, overruling, and current policy inside FalkorDB. Also exposes graph analytics, agent memory and handoffs, policy-impact simulation, and hash-chained ledger verification as MCP tools.

Pay-per-thought AI second opinions for autonomous agents. Agents pay 0.01–0.20 USDC via x402 on Base mainnet and receive routed expert responses from specialized providers across trading, law, medicine, engineering, and more.

A self-aware, AI-powered MCP server that acts as a personal medical education assistant for African students, understanding natural language and autonomously managing reminders, data bundles, and medical knowledge retrieval.

A Model Context Protocol server that allows AI models to log and retrieve contact events with various authorities (police, fire, medical, etc.) with rate limiting and persistent storage via Supabase.

Enables law firm staff to automate case intake, conflict-of-interest checks, and attorney assignment through secure MCP tools without exposing sensitive data directly to LLMs.

An intelligent hospital appointment management system that allows users to add doctors/patients, book appointments, and view medical schedules through both a manual UI and an LLM-powered assistant interface.

Enables an AI assistant to dynamically discover and invoke MCP tools for document search, employee information lookup, and mathematical calculations, with human-in-the-loop approval for sensitive operations.

Provides real-time, privacy-preserving analysis of LLM interactions to detect problematic behaviors like medical advice, dangerous file operations, physics speculation, and unsupported claims. Recommends safety interventions and builds a taxonomy of LLM limitations through crowdsourced evidence collection.

Provides AI-powered medical consultation and clinical decision support through diagnostic analysis and personalized healthcare recommendations using OpenAI integration.

Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.

Enables LLMs to communicate with Agent-to-Agent (A2A) protocol compliant agents, providing tools for sending messages, managing tasks, and retrieving agent information.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.

Gives LLMs a genuine in-game seat in Civilization V, letting them scout, settle, negotiate, fight, and manage a civilization through tool calls with the same fog-of-war information a human player sees.

Enables LLM assistants like Claude to interact with Zaif cryptocurrency exchange through natural language, supporting market information retrieval, chart data, trading, and account management for BTC/JPY, ETH/JPY, and XYM/JPY pairs.

Lets MCP clients ask typed questions — yes/no, choice, or score — about structured state, including images, and receive calibrated probabilities from System One decision models such as TypeSafe Jev and Cloudflare Clef. Supports TypeSafe, OpenRouter, and local providers selectable per request, with input validation and cost reporting.

Enables agents to store and recall long-term memories by semantic relevance rather than exact keywords, with writes gated by verbatim evidence and separate memory stores per agent mode.