"A resource for analyzing Polish legal acts" matching MCP servers:

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 AI assistants and agents to search a legal document collection via hybrid BM25+dense retrieval, read articles with context, and generate full or short citations. It also exposes whole acts as Markdown resources, provides a citation-answering prompt, and supports stdio and streamable HTTP transports.

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

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 Also provides exact lookup of administrative interpretations with lifecycle status (repealed / superseded / unverified).

Enables law knowledge Q&A with traceable, citation-verified answers from a shared 38-law article-level index, plus single and batch police incident risk assessment grounded in retrieved statutes. Exposed as stdio MCP tools (law_qa, risk_assess, risk_assess_batch) for dsh, Claude Desktop, Cline, and other MCP clients.

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.

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.

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.

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 proof of concept MCP server for Apache OFBiz

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

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 production-ready foundation for building secure, observable MCP servers with built-in authentication, rate limiting, and reference tools like database-query and semantic-search.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

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.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables secure access to legal documents from Clio via Claude Desktop, with local processing and semantic search to ground AI responses in actual documents.