"Slack Bot with RAG Document Retrieval and Automated Response System" matching MCP servers:

Enables intelligent document processing by extracting text, classifying document types, and generating structured summaries from PDFs and images using vision LLMs.

Enables clients to inspect local PDFs by searching text, rendering pages, and cropping selected regions at high resolution directly from the source document. It runs locally over stdio without requiring models, embeddings, GPUs, or API keys, and does not modify source PDFs or send network requests.

Enables MCP clients to generate and edit images through Codex's built-in image generation using a ChatGPT login, returning final files with metadata and optional inline previews.

Enables agents to extract multi-page financial tables from complex PDFs, rasterize vector pages into crisp 300 DPI images for vision LLMs, flatten interactive AcroForm/XFA forms, and dewarp skewed OCR bounding boxes from photographed or scanned paper documents. Tool invocations are gated by USDC micropayments settled on Base L2 via the x402 protocol.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

An AI-powered MCP server that extracts structured data from Indian identity documents (Aadhaar, Passport, PAN, Driving License) using OCR, enabling Claude Desktop to read and process document images locally.

MCP server for MarkItUp's AI image-annotation pipeline. Generate polished marketing-visual variations of any screenshot, regenerate, AI outpaint, and remove backgrounds — powered by Claude analysis + Gemini rendering.

Enables AI agents to create and edit pixel art in a live Aseprite window, with tools for drawing, selection, transformation, and animation.

Enables high-quality 3D-style cartoon image generation using Google Gemini AI alongside secure file system operations like reading, writing, and managing directories. It provides a dual-purpose toolkit for creative asset generation and local file management via the Model Context Protocol.

MCP server that exposes Google's Veo2 video generation capabilities, allowing clients to generate videos from text prompts or images.

Enables AI agents to assess document image clarity, detect defects like blur and glare, and either pass clean documents to OCR or provide multilingual corrective guidance for defective captures.

Provides AI-powered subsurface scan analysis and plain-English bid drafting tools, helping certified technicians assess hazards and trades build estimates.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

Enables deterministic visual and structural analysis of PDF and DOCX documents, extracting measurable evidence such as blur, OCR confidence, and image anomalies for auditable forensic workflows.

Enables text-only agents to process images by accepting image files, base64 data, or URLs, sending them to multimodal models, and returning structured text results via MCP.

Enables driving Inkscape headlessly from an MCP client, with verified SVG editing, rendering, optimization, and animation tools.

MCP server that lets AI assistants control Adobe After Effects via natural language, enabling composition and layer creation, animation, effects, presets, rendering, and arbitrary ExtendScript execution with Arabic/RTL support.

Enables Claude to analyze reference videos (download, transcripts, frames) and generate new branded Instagram Reels/YouTube Shorts as React/TSX compositions, rendered to MP4 via Remotion.

Deterministic file operations for AI agents: 40 operations over plain HTTPS. PDF merge, split, redact, sanitize, OCR, Office and PDF to Markdown, RAG chunking, charts, QR codes, C2PA AI labelling. find_tool suggests the right one. $0.01 per operation, 100 free, no signup, credits never expire.

Reads passports, ID cards and driver's licences from a photo or scan and returns the printed fields and MRZ as structured JSON. One credit ($0.01) per recognised document; nothing is charged when no document is found.