"A server for searching US law and legal documents on Justia" matching MCP servers:

Enables AI assistants to search and analyze German legal texts using vector embeddings and semantic search.

MCP server for evidence-based Chinese legal consultation. It routes labor law questions to a knowledge base and other queries to public search, returning answers with citations and fallback reasons.

Semantic and exact retrieval over 22M Taiwan court judgments with built-in citation guardrails — bundles carry a read-whitelist so downstream models cannot cite judgments whose reasoning was never read. Also provides exact lookup of administrative interpretations with lifecycle status (repealed / superseded / unverified).

An AI-powered MCP server for analyzing Japanese legal contracts and identifying risks through a RAG-enhanced workflow. It enables clients to search legal knowledge, analyze clause risks, and generate automated contract review reports.

Enables semantic search over Turkish legal contracts and emails via an MCP server integrated with Claude Desktop and Claude Code, providing tools for document ingestion, hybrid vector search, and full-text retrieval.

A comprehensive Model Context Protocol (MCP) server implementing the latest MCP specification with tools, resources, prompts, and enhanced sampling capabilities that features HackerNews and GitHub API integrations for AI-powered analysis.

Enables natural language interaction with the Korean Personal Information Protection Act (PIPA) through 37 MCP tools that search, compare, analyze, and verify legal texts, official guidelines, and consulting cases from authoritative sources.

Enables intelligent search and retrieval of Japanese legal statutes through the e-Gov API. Supports smart lookup of laws and articles with abbreviation recognition, batch processing, and multi-tier caching for high-performance legal research.

MCP server providing access to US patent data (2000-2024) via Rememberizer's knowledge retrieval tools, enabling semantic search and document management for patent information.

A proof of concept MCP server for Apache OFBiz

This read-only MCP Server allows you to connect to Act-On data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

An Operit-compatible adapter of the Exa MCP server, enabling web search, code search, and company research capabilities in AI assistants. It fixes MCP handshake compatibility issues, allowing tools like web_search_exa and web_fetch_exa to load and run reliably.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

MCP server for retrieving and verifying audit regulations, clauses, and audit items using vector and relational databases.

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.