"Supabase (open source Firebase alternative)" matching MCP servers:

MCP server for reading public Featurebase feedback boards, enabling agents to query user feedback, posts, comments, and statistics.

Provides MCP tools for AI agents to create and read decision decks, propose cards and build plans, and retrieve finished tasks, enabling local decision review workflows with portable task handoffs.

Manages and authoring of business rules in a scenario studio tool, enabling agents to read, update, link rules, and assign them to capabilities via MCP tools.

Enables AI assistants to search and retrieve verified software comparisons, including current pricing with source and date, and ranked alternatives for software switching decisions.

Open source MCP server for OpenProject aimed at community edition users

An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.

A local MCP server that gives AI agents read access to Roblox experience analytics via the Open Cloud API, exposing 168 metrics and analysis tools for retention, engagement, monetization, and more.

This MCP server enables users to keep one source of truth for their experience and generate role-tailored, ATS-safe PDF and DOCX CVs, with enforced skill levels, job-post gap reports, and build verification.

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.

Mogut — open-source, read-only MCP server for Apple App Store ASO and growth intelligence: keyword research, competitor analysis, review mining, pricing, localization, and reports.

Enables customer-success teams and AI hosts to inspect account evidence, assess onboarding readiness, assemble unsent bilingual follow-up drafts, and prepare traceable technical handoffs through scoped MCP tools. It preserves source references and distinguishes recorded failures, missing evidence, and possible explanations for human review.

Enables Claude Code to run multi-round grilling sessions in a browser UI, publishing rounds of questions with options and recommendations that users answer with buttons or free text. Supports per-question asides (re-pitch, visual diagram, plain-language explainer), chat notes between rounds, and a polling contract so sessions can stay open without blocking the client.

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.

Lets AI clients draft, inspect, edit and review wireframe/storyboard boards over MCP, sharing one live board with the app the user has open. It also supports loading boards back, resolving review notes, and exporting realistic previews so specs can be iterated from natural language.

Enables users to transform raw multi-source enterprise findings into complete, structured strategic documents, auto-generating executive summaries, risk registers, decision matrices, and appendix citations. It runs as a zero-dependency Python MCP server that works with Claude Desktop, Cursor, and other MCP-compatible clients.

Enables auditing AI products against a 12-criteria human-impact rubric and generating 0–100 scores, evidence-backed or provisional badges, and shareable teardowns from structured findings and source URLs.

A single source of truth for a product's state, roadmap, and deferred work, read and written equally by you and your AI agent via web dashboard and MCP.

Enables agents to discover and validate SaaS opportunities mined from real user complaints across eight public sources, scoring ideas for commercial intent. Also allows fetching detailed dossiers on specific gaps with source complaints, MVP scope, pricing, competitors, and risks.

Turns the five Playing to Win boxes into queryable data over MCP: list all positions, open one position with its supporting, opposing, and complicating evidence, adopt or reject it with a note, record new evidence, add positions into a box, and organize several cascades of boxes. Read and write tools share the same core and query layer as the CLI and web pages, so every surface stays consistent.

Turns a rambling app idea into a structured planning canvas of screens, flows, systems, data and open questions inside an existing Claude Code or Codex session, then writes the settled plan back to that session as a spec to build from. Plans are stored in the project's .doan/ folder alongside the code.