"An introduction to Laravel framework" matching MCP servers:

Enables agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

An AI-native product development pipeline that guides users from idea to shipping with structured research, architecture, build, validation, and traceability using 52 tools across 4 domains.

Enforces a marketing pre-flight: plan the campaign with kill criteria, score each offer on an explainable 0-100 rubric, and require every tactic to cite a scored offer plus a success metric before any spend.

An MCP server for accelerator programs to query, review, and manage startup applications via natural language. It enables searching applications by sector or impact score, fetching full application details with reviewer notes, listing pending reviews, and flagging applications for panel discussion.

Enables AI clients to create AI-powered forms from natural language descriptions, preview, publish, and close them, and then list, summarize, and export collected responses as CSV. It ships nine tools so an agent can run a form end to end.

Turns product feedback pinned to a live UI into an actionable backlog for Claude Code — list comments, open one with its target element's HTML, computed styles and screenshot, and update its status.

Lets an AI agent read a Pyxis dashboard's analytics — overviews, funnels, devices, acquisition, backend requests, visits and project settings — using a read-only access token created by an admin and revocable at any time. It runs locally over stdio, holds no state, and exposes only GET-style reads of the live Pyxis API.

An MCP server that enables AI tools to interact with the Lalaleap project management system using natural language, allowing creation and management of requirements, bugs, todos, and projects.

Enables AI assistants to search, de-duplicate and route leads in a demo CRM, with read-only mode and an audit log for accountability.

An MCP server for the Trello REST API. Exposes ~36 curated tools for boards, lists, cards, checklists, labels, members, and search.

An MCP server that connects Claude to ProdPad, giving Claude direct access to your product management data including ideas, feedback, roadmaps, OKRs, and initiatives.

Guides product design through mandatory phases—discovery, definition, prioritization, flows, and verification—so an AI assistant can run a project from problem to verified scope, with strict or free progression modes.

Connects AI coding tools to an Atono workspace, offering 41 tools to read and write stories, bugs, epics, subtasks, acceptance criteria, timeboxes, glossary, and AI context so agents work with real product knowledge.

Build surveys, read responses and make reports in SurveyNinja from your AI assistant. Describe a survey in plain words, check it before launch and publish it, then read the responses, get a summary or an AI report and export the results to CSV, Excel, SPSS or PDF. Hosted server, sign in with OAuth or an API key; works on every plan, Free included.

Provides an MCP Apps interface to the Upvote Club API, enabling task management with an inline progress card UI in Claude.

A User Story Map and Kanban board that a human and an AI coding agent plan together in real time via MCP, with live bidirectional sync and governance enforcement.

Enables group food ordering by interpreting group messages and private budgets, matching requests to menu items, and computing an exact optimized order across at most two restaurants while enforcing per-person spending limits and minimum-order rules.

A demo MCP server exposing an in-memory todo list via tools (add_task, list_tasks, complete_task), a resource, and a prompt, over both stdio and HTTP transports.

An MCP server that exposes a Proof workspace to MCP clients, enabling tools for reading/writing concepts, managing ideas and projects, running ideation operators, and more, with live sync and headless authentication.

Official MCP server for Weft, an agent-first Scrumban board. Agents claim tasks with leases, report progress, and finish with receipts you accept or return from an Inbox. Hosted remote endpoint, OAuth 2.1, no API keys.

An MCP server that exposes Google Play Console analytics to AI agents, including store-listing acquisitions by traffic source, installs, uninstalls, ratings, crashes, subscriptions, and reviews by reading bulk CSV reports from Cloud Storage.

Enables AI orchestrators to manage hierarchical implementation roadmaps with phases, tasks, and plan-change tracking.

Enables AI agents to query Mixpanel event data, funnel conversion rates, and retention cohorts via MCP tools or natural language.

Enables ChatGPT to initiate a visible, evidence-backed UI/UX audit by returning an exact workspace URL through a read-only start_audit endpoint, where page-scoped Site Tools can measure and judge the target without claiming capture.

MCP server for noise-reduced X (Twitter) search planning and Feedback-to-Fix engineering handoffs. Enables AI agents to generate structured search plans, filter signals, and build handoff packages via MCP tools.

Enables AI agents to guide users through pretotyping, turning raw ideas into Lean Canvases, testable hypotheses, and small experiments to validate demand before building.

Connects an AI assistant to a dealer account so it can build and link a shop website that shows live vehicle stock and takes enquiries and test-drive bookings with no database to run. It also lets the assistant read and change listings, prices, test drives, reviews and leads in plain language, with read-only access by default and every change written to an audit log.

Enables AI agents to run a full QFD session over the Model Context Protocol: build and edit a House of Quality (stakeholder needs, measurable characteristics, relationship cells, trade-off roof, work items), validate it, and read back priorities, gates, the diagonal build order and item progress. It also exports the house as TSV, CSV, JSON, SVG or an Excel workbook, with optional file persistence so a person can keep editing where the agent left off.

Enables AI assistants to manage projects, tickets, tags, and relative weight prioritization calculations, with revision history and multi-project support.

Turns an unstructured business note into deterministic, explainable signals for revenue, automation, risk, urgency, and data, returning a score, priority, evidence, and a suggested next action. This lets an AI assistant assess and prioritize business opportunities through an auditable, locally computed tool.