"Document analysis tools for legal documents and evidence" matching MCP servers:

A local document evidence layer for MCP clients that ingests documents (PDF, Office, images) with optional OCR, indexes them in SQLite FTS, and provides retrieval tools with source coordinates.

A Model Context Protocol server that provides document analysis capabilities to LLM applications, including extraction, chunking, summarization, and semantic search for PDF, DOCX, and plaintext documents.

Enables interactive chat with AI models, including document retrieval and command-based prompts via the Model Control Protocol.

Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.

Provides MCP tools to search local document corpora with conservative semantic deduplication, source retention, and version/scope filtering, returning compact evidence packets with original passages and source IDs for agents.

Enables local read-only search and retrieval of approved, current evidence via hybrid lexical and dense methods, with tools to get exact source spans, answer from cited passages, and create and verify recheckable evidence packets.

Enables AI assistants to search a library of over 20,000 open legal skills by keyword, by meaning, or a hybrid of both, filtering by jurisdiction, language, practice area, or tag. It also returns facet counts for the collection and retrieves the full text of any selected skill.

Enables agents to search and reference trusted, out-of-band ingested source state, run claim-bound document reviews, validate evidence-status proposals against admissibility guards, and build evidence matrices. It keeps proposal, evidence, admissibility, and adjudication separate so agents can propose epistemic statuses without creating the source facts, page locators, provenance, or missingness records that support them.

Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.

Enables natural language search and analysis of uploaded PDF, CSV, and Excel documents using retrieval-augmented generation and MCP tools, providing contextual answers to user queries.

Provides medical evidence tools including PubMed search, citation verification, clinical trial lookup, drug information, drug interaction checking, PICO extraction, and medical entity recognition via MCP.

Enables AI agents to discover, inspect, compare, and resolve local fonts and typography through bounded search, paging, family inspection, exact assets, contextual compositions, and preview images, while keeping fonts and model inference local.

Enables AI assistants to retrieve cited official statistics from any SDMX 2.1 API and to search policy documents through a local retrieval index with a sensitivity ceiling.

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

Enables searching Bilibili videos by question and retrieving specific timestamped segments that answer it, with direct jump-back links. It performs local transcription, caching, and Chinese BM25 ranking to provide precise video evidence without external APIs.

Enables reading and searching documents in allowlisted folders via LiteLLM and MCP tools, using COM for Office files to support IRM-protected content.

Enables semantic and keyword search over legal documents, conflict detection, and document overview, supporting Indonesian and English texts.

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.

Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.

Enables local-first, versioned evidence retrieval from papers without loading the whole library into a conversation, with optional Zotero, writing, fixed-commit code, and experiment record integration returning bounded excerpts and page images.

Provides AI agents with multi-format document indexing, hybrid dense and sparse search with reranking, and relational SQL querying over extracted tables.

Enables MCP clients to search, read, and record reviewed conclusions from policy-gated allowlisted files, with sanitized chunks and create-only drafts or append-only lessons, without granting general filesystem or execution access. It supports lexical ranking and optional loopback embeddings while rejecting likely credentials and raw challenge flags.

Provides read-only, authenticated access to prepared Markdown, images, document structure, and original-file references published as immutable versioned bundles alongside Paperless-ngx source documents. It can also explicitly forward selected prepared Markdown into WeKnora's existing ingestion interface without subscribing to future documents.

Search a folder of documents and check answers against them. Offline: no API key or database.

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.

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 real-time indexing and semantic search of local documents (PDF, Word, text, Markdown, RTF) using vector embeddings and local LLMs. Monitors folders for changes and provides natural language search capabilities through Claude Desktop integration.

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 NPC agents to read, write, search, and manage a shared corporate document store, and to turn Mission Scripts into structured report outlines and scaffolds aligned to strategic intent.