"Guide to GCP Resource Management and PaaS Setup and Configuration" matching MCP servers:

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

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

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Your agent takes a business live on payments: go_live creates a real merchant account (sandbox + production) the same day; create_checkout returns a payable link. Payments for AI builders, 3.9% flat.

Enables AI agents to manage Google Cloud Platform resources including projects, IAM, service accounts, and APIs directly through GCP REST APIs without requiring gcloud CLI or Terraform.

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.

Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.

Enables managing Google Cloud Platform (GCP) resources through natural language commands, including compute instances, storage, databases, and monitoring.

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.

Enables auditing a repository's Claude Code setup, scoring it from 0 to 100, and scaffolding agents and hooks to fix issues.

A local MCP server for read-only querying of AWS resources (Lambda, S3) via Boto3, currently exposing a health check tool with planned tools for listing resources and checking free tier.

An automation tool for macOS that uses AppleScript and JXA to manage Discord server setups through AI assistants. It enables the creation and configuration of servers, channels, roles, and settings using pre-built templates or custom commands.

Automates setup of local development environments for Python, Node.js, Flutter, Android, and more on macOS and Linux. Can be used as a standalone CLI or as an MCP server for AI assistant integration.

Provides access to the Reuters Business and Financial News API to retrieve articles, trending news, and market data. It enables searching and filtering financial content by date, author, category, and keywords.

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Estimates physical quantum resources (qubit count, runtime) for quantum algorithms on fault-tolerant hardware through natural language queries.

License-aware game development resource discovery MCP server. Helps AI coding agents find reusable game assets with commercial-use filtering, license classification, and attribution generation.

An MCP server that transforms books into agent-callable skill packages, enabling AI agents to use books as guides for evidence, procedures, and tutoring.

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.

Exposes employee leave-management operations (add employees, check balance, apply/cancel leave, view history) as MCP tools for AI clients like Claude Desktop to call directly.

Give AI agents cited funding, money-market, FX and capital-market evidence through 16 public MCP tools. Keep source dates, freshness checks and coverage gaps attached; China macro coverage is metadata-only. No API key is required for the public surface. Research context only; no trade execution.

Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Enables an assistant to watch a cooking video once and then guide a hands-free cook through it: importing videos into validated step-by-step guides, navigating steps, searching timestamped transcript and on-screen evidence, showing exact frames and clip replays, and setting persistent timers across restarts. Sessions, progress, and deadlines are stored so users can resume where they left off.

Complete Vinted MCP and CLI Server

Connects AI assistants to your n8n instance to manage workflows, executions, credentials, and user settings through 31 specialized tools. It enables users to perform n8n operations like workflow creation, activation, and execution history retrieval via natural language.

Integrates Azure Cost Management APIs via MCP, enabling cost queries, forecasts, budgets, and Advisor recommendations through natural language in compatible clients.

MCP server that exposes GDB debugging as tools. An AI assistant can set breakpoints, run programs, step through code, inspect variables and memory, and examine registers — all via structured tool calls. Reverse debugging with rr is also supported.

Manage Job using MCP: Manage Job, Candidates, Resumes, Salaries all within this one MCP tools It can solve problems like: You have 50 resumes to screen. Your AI assistant can reason about candidates, but it can't: Read PDFs/DOCX — The AI can't open binary files Extract structured data — Copy-pasting loses formatting, metrics, and context Compare at scale — No consistent scoring across candida