"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 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.

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 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.

This MCP server enables reading and analyzing various file formats, including PDF, DOCX, XLSX, and CSV, by extracting metadata, searching for keywords, and reading structured content. It also provides capabilities to create new documents and convert files between supported formats.

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 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.

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.

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.

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.

A local AI document assistant MCP server that enables listing, reading, and editing documents via tools, resources, and prompts, allowing LLMs to manage document workflows through natural language.

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 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.

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 locally recording requirements, decisions, checks, and AI proposal assessments, then running bounded verification and exporting traceable review packets without external API keys or remote services.

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.

Enables keyword search across source-traceable evidence chunks, listing opportunities linked to supporting evidence, and deterministic ROI calculations with model-proposed inputs and TypeScript-computed dollar figures.

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.

Unifies 14 Argentine legal connectors (JUBA, SCBA, CSJN, SAIJ, PJN Jurisprudencia, BORA, BOPBA, InfoLEG, Normativa PBA, PTN, TFN, PJN Consulta, Portal PJN, JusCABA) into a single MCP server for Claude Desktop, enabling local, read-only access to jurisprudencia, legislation, and legal documents.

Enables AI assistants to run local, model-backed decisions on short passages and routing choices, and to check whether exactly supplied text supports a scientific claim, returning the full probability distribution, review-policy status, and provenance details. All evaluation stays on the local machine with no cloud inference, and flagged results are surfaced for human review rather than treated as conclusions.

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.

A no-server MCP toolkit that organizes project wikis from Feishu documents, messages, and more, enabling AI clients to answer questions with cited evidence to prevent hallucinations.

Enables local, read-only checks of financial disclosure claims against fixed research snapshots, including cutoff queries, operating metric scope, cash-bridge arithmetic, claim tracing, and replayable evidence packets.

Enables AI agents to run evidence QC gates mid-workflow—checking claims, sources, prose, and vault hygiene deterministically before research ships.