"Extracting Orders from PDF Files" matching MCP servers:

* taniwhaai/arai 🦀 🏠 🍎 🪟 🐧 - Policy enforcement for AI coding agents derived from existing instruction files (CLAUDE.md, .cursorrules, .windsurfrules, .github/copilot-instructions.md) — no separate YAML to maintain. Rules with prohibitive predicates (never, forbids, must_not) emit permissionDecision: deny to block tool calls in Claude Code; advisor

Provides coding agents with repository context through tools that generate AGENTS.md files or structured JSON summaries, quoting build/test commands from the repo's manifests for a small fee without an API key.

Generates AnyLogic simulation models from natural-language prompts in Claude Code, allowing users to describe queueing systems, factories, or ERs and obtain runnable .alp files.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

A Model Context Protocol (MCP) server providing 62 AI-optimized tools for .NET/C# semantic code analysis, navigation, refactoring, and code generation using Microsoft Roslyn. Built for AI coding agents - provides compiler-accurate code understanding that AI cannot infer from reading source files alone.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

Gives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.

Enables AI coding agents to debug Python projects by running pytest, extracting failure locations, displaying code context around failures, and optionally requesting fix suggestions from Gemini.

Enables Claude.ai to interact with the Cursor editor to read files, write code, get selections, and more.

Vyuha is an MCP server that enables coding agents to collaborate on a repository by providing tools for ticket creation, worktree management, code review, and staged deployment, all from local files.

Enables Claude Code to research design references per page section across galleries like Awwwards, Dribbble and Mobbin, render the user's page in multiple style directions with live 3D components, and collect votes on a local board. It then produces a PDF report and iteratively builds and refines the actual page, dashboard prototype or mobile screens from that feedback.

Enables coding agents to open files and git diffs directly in VS Code, allowing users to review code changes without leaving their conversation.

A local vector database system that provides LLM coding agents with fast, efficient semantic search capabilities for software projects via the Message Control Protocol.

Enables agent-style remote development over SSH with file operations and command execution, exposing native tools for searching, editing, and transferring files on remote machines.

Enables users to run shell commands with compressed output, extract information from large files, drive local opencode and Codex agents, perform browser-automation tasks, and monitor runs via a live dashboard.

Enables AI coding agents to conserve tokens by enforcing rules like delegating heavy work to subagents, checkpointing before token limits, and grepping before reading files.

Enables task-specific coding agents defined in Markdown files to be run from any MCP-compatible client, executing them with a chosen coding CLI backend and returning the result to the same conversation. The same agent definitions can be reused across clients with shared backend and model configuration, and continued across multiple calls through sessions.

A project intelligence platform for AI coding agents that scans, audits, generates, and monitors context files (CLAUDE.md, AGENTS.md, etc.) with drift detection and repair capabilities.

Connects ChatGPT to local files, terminals, and the desktop through MCP with Chrome integration, letting users read and edit project files, run commands, and follow tool results as they arrive. It also adds durable multi-agent workers, Goal/Loop task tracking, mid-task corrections, and Compact & Resume for carrying session and worker history into a fresh chat.

Enables users to define task-specific agents in Markdown files and run them through a chosen coding CLI (Codex, Claude Code, Cursor, and others) from any MCP-compatible client, with results returned to the same conversation. Supports shared model and permission settings plus optional session continuity across multiple calls.

Enables users to run reusable, task-specific coding agents defined in Markdown files from any MCP-compatible client, executing them through a chosen coding CLI backend and returning the result to the same conversation. Supports shared backend and model configuration, permission levels, and session continuation across multiple calls.

Enables running and supervising pi coding agents over RPC, with hot resume, cold resurrection from session files, sandboxed execution, lifecycle counters, and log/artifact inspection.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

A token-efficient, codebase-aware AI agent runtime that provides MCP tools for starting runs, getting run states, explaining code, and finding files.

Lets you define reusable, task-specific coding agents in Markdown files and invoke them from any MCP-compatible client, running each one through a chosen coding CLI backend and returning the result to the same conversation. Supports shared backend and model settings, permission modes, and optional session continuity so an agent can continue work across multiple calls.

Enables users to define task-specific coding agents in Markdown files and invoke them from any MCP-compatible client, running each agent through a chosen coding CLI and returning results to the same conversation. It supports reusable agent definitions with shared backend, model, and permission settings, plus session continuity across multiple calls.

Enables running reusable, task-specific coding agents defined in Markdown files from any MCP-compatible client, executing them with a chosen coding CLI backend and returning results to the same conversation. Supports configurable backends, models, permission levels, and session continuation for longer tasks.

Enables managing Linux hosts and local coding agents from an MCP client through shell commands, files, background jobs, system information, instruction and skill discovery, and optional Claude Code, Codex, or Cursor CLI conversations. It provides privileged remote access with token authentication and can run longer work in the background.

Easily create custom reusable automation tools from casual browser actions using Apify Agent. Automate workflows by running your recorded actions turned into MCP tools.