"How to read PDFs and images" matching MCP servers:

An MCP server for analyzing images using OpenRouter vision models, offering capabilities like automatic image resizing, model configuration, and handling custom queries about images.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A Model Context Protocol server that extracts images from URLs or base64 data and converts them into a format suitable for LLM analysis, allowing AI models to process and understand visual content.

Enables AI assistants to generate and edit images using Google's Gemini 2.5 Flash Image API with intelligent prompt enhancement. Supports text-to-image generation, image editing with natural language instructions, and advanced features like character consistency and multi-image blending.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables Codex to delegate coding tasks to an OpenCode CLI locally, returning structured results such as exit codes, session summaries, tool calls, and git diffs.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Allows AI assistants to generate and transform high-quality images from text prompts using Google's Gemini model via the MCP protocol.

Enables routing tasks to the right specialist agents, assembling the needed context from a layered catalog of agents, skills, knowledge, runbooks, topics, tools, and connectors, while remembering how a business wants work done.

Teach any AI agent how you use an MCP server – Soft-Landing to your AI integrations

Lets AI agents launch scans, inspect results, manage campaigns and policies, and read alerts directly against your Kaminari Ad workspace via your API key, with 82 tools covering most of the API surface.

Enables AI agents to publish posts, images, comments, and reactions to LinkedIn as the authenticated user, with built-in safety features like daily budgets and deduplication.

Enables learning how to build and use an MCP server with tools, resources, and prompts through a Python example.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

Enables local job-search automation, from finding and scoring postings to drafting tailored CVs and cover letters, compiling PDFs, and tracking applications through your AI assistant.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

An MCP server implementation that integrates with 4o-image API, enabling LLMs and other AI systems to generate and edit images through a standardized protocol. Create high-quality art, 3D characters, and custom images using simple text prompts.

Empower LLMs with fine-grained visual understanding — detect, localize, and describe anything in images with natural language prompts.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.