"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.

Legal Document AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

An MCP server that converts and processes document formats such as DOCX and PDF into Markdown, enabling AI assistants to work with document contents.

MCP server for document conversion and processing, enabling AI assistants to handle various document formats.

Enables AI assistants to convert and process various document formats through an MCP server interface.

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.

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.

A remotely callable MCP server for US legal research that provides tools to search, retrieve, and analyze US case law from the CourtListener API, enabling agents to build evidence packs from primary sources without generating legal content.

A production-ready Model Context Protocol server that bridges local document management with cloud synchronization (Notion) for AI agent integration, enabling seamless access and sync of local and cloud documents.

Safely downloads and extracts public tender documents from PDFs, Office files, and ZIP archives into text with structured signals, while also supporting document comparison and base64 extraction.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Enables analysis of legal document changes by constructing a dependency graph and simulating impact propagation, with risk level assessment.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

Verifies legal citations by fetching the exact, in-force wording of cited articles from official PL and EU legal sources, preventing hallucination by returning verbatim text.

An MCP server that exposes documents.js's document conversion, .odb, metadata, and font tooling as MCP tools, enabling agents to convert, inspect, and edit a wide range of document formats over stdio.

Drives a real Chromium browser via Playwright to capture evidence (screenshots, video, trace) of feature verification sessions.

Public MCP research for AI finance and trading agents: funding, bank risk and liquidity evidence. Companion SDK: persistent Python MCP sessions and Python/JS source-status streams. Setup: https://beepboop2025.github.io/financial-evidence-skills/distribution/ai-trading-tools.html. No data API key. Keep source dates, rights and gaps. No live quotes or execution.

Enables AI coding agents to assemble tamper-evident, locally stored evidence bundles that capture Git state, command results, and file hashes, then verify freshness and export shareable reports.

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.

A multi-format MCP server that enables reading and generating Office, PDF, text, EPUB, and presentation documents. It provides unified tools for document processing and creation through AI assistants.

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

Enables deterministic research of Korean tax-law issues by retrieving and scoring official statutory evidence from law.go.kr and other legal sources, with citation verification and provenance, without deciding legal conclusions.

Enables AI assistants to create Evidence reports and dashboards by providing tools to query database schema, read documentation, edit pages, and debug code.

Enables read-only collection and comparison of Google Search Console and Bing Webmaster data, conservative URL protection, content auditing, reviewed-build verification, and private report generation through ten typed tools over stdio.

Full-text search and retrieval over official congressional documents (hearings, committee reports, Congressional Record) with citations and govinfo.gov links, designed for grounding AI answers in the official record.

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.

A stateless MCP server for composing, validating, auditing, and rendering consequential documents from a small semantic model.

Enables coding agents to select bounded Python source context, run configured checks, and retrieve compact failure reports, diagnostic comparisons, and freshness evidence tied to the checked code.

The local PDF workflow for Claude Desktop and MCP hosts: fill, sign, merge, split, extract, and analyze PDFs without sending files to a web app.