"A service for document recognition, assessment, and filling in evaluations" matching MCP servers:

MCP server for intelligent circuit diagram recognition, enabling detection of components, text, topology, and netlist from circuit images.

An MCP server that provides local image recognition on macOS, including OCR, image classification, comprehensive image analysis, and screenshot recognition, all via Apple's Vision framework without any network requests.

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.

Enables pediatric CKD nutrition assessment by calculating PRNT energy/protein targets, evaluating dietary intake against those targets, and screening for PEW risk, with support for dialysis, vegetarian diets, and edema corrections.

Gives vision-less LLMs the ability to recognize clipboard screenshots and images by proxying to an OpenAI-compatible vision model.

A persistent 24/7 background daemon that aggregates all downstream MCP servers into one unified connection and layers on a real-time notification gateway so AI agents can receive events from X/Twitter, Slack, Email, and webhooks.

An MCP server over stdio that exposes strictly validated tools, using Pydantic models as both schema and validator and returning -32602 for invalid arguments.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Enables document format conversion between Word, Markdown, PDF, HTML, and plain text, supporting batch operations and format validation via the AI MCP protocol.

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.

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

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

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.

A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.

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 Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

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.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Converts PDFs, Office files, spreadsheets, emails, audio, and more to Markdown locally, enabling AI assistants to read and process them without cloud upload.

Enables AI agents to efficiently manage and update component documentation with precise partial updates, saving up to 75% tokens compared to full rewrites.