"Planning a Trip and Booking a Hotel" matching MCP servers:

Hotel booking MCP server — the first transaction-complete hotel booking integration for AI agents. Search 300K+ properties in 140+ countries, get live rates and room details, and generate secure checkout URLs. No payment in the AI conversation — guests complete booking at a hosted checkout page and receive a real hotel confirmation number. Set your own booking fee via Stripe Connect.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

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.

An MCP server that facilitates interactive software development planning by breaking down projects into manageable tasks, tracking progress, and saving implementation plans.

Facilitates software development planning through interactive sessions that break down projects into manageable tasks with complexity scoring, code examples, and implementation plan management.

Facilitates interactive software development planning by managing tasks, tracking progress, and creating detailed implementation plans through the Model Context Protocol.

Transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement. Guides users through clarifying questions to gather comprehensive requirements for automated Business Intelligence dashboard generation.

Provides software development planning tools to help users create implementation plans and manage todo items.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

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

Enforces a rigorous spec-driven engineering workflow for AI coding assistants, requiring requirements, design, and task planning before any code is written.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Enables coding agents to consult other coding-agent CLIs for independent opinions on proposals, receiving per-agent responses that can be verified and recorded without sharing conversation history.

Enables AI agents to design and critique websites using 2026 trend reports, motion code recipes, design principles, palettes, type systems, section skeletons, references, and DESIGN.md tokens, with performance and reduced-motion handling built in.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables AI agents to create, manage, and search hierarchical plans with phases, tasks, and milestones through a comprehensive planning API. Supports CRUD operations, batch updates, rich context retrieval, and artifact management for structured project planning.

Gives AI coding agents typed, mode-gated access to a real WordPress site — content, media, users and settings via core REST, plus PHP execution, SQL queries, filesystem operations and Elementor page read/build/patch/snapshot via a companion bridge plugin. Destructive actions and code execution are guarded by feature flags, explicit confirm literals, dry runs, redaction and audit logging.

A lean, local knowledge graph that joins a repo's code to its aSPARK delivery artifacts, enabling agents to trace user stories to code and assess impact of changes, served over MCP.

A MongoDB MCP Server that allows AI agents and MCP clients to interact with MongoDB databases through standardized tools for CRUD operations, schema discovery, and collection management.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

MCP server for deterministic, zero-dependency context-window math, enabling token estimation, text truncation, and budget reporting without a tokenizer.

Provides structured task planning and tracking capabilities with 40 tools for managing requirements, solutions, architectural decisions, and hierarchical implementation phases with progress tracking.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

Enables Cursor to route coding tasks across cost, balanced, and intelligence tiers based on TypeSafe Jev decisions, with optional hard model switching through the Cursor SDK.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

A Model Context Protocol server that enables AI assistants like Claude to read from, append to, and format text in Google Documents programmatically.

Generates a pytest suite from acceptance criteria withheld from the coding agent, so the tests can disagree with the code; qikly_run never returns the criteria. The CLI also scores an existing suite by planting faults, and ships as an agent Skill (qikly --install-skill). Runs locally (uvx --from "qikly[mcp]" qikly-mcp): your code and API key stay on your machine.