"Guidance on connecting to Databricks" 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.

It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.

Enables creating, managing, and analyzing live audience surveys on rifts.to directly from an AI client. Supports creating surveys, listing them, retrieving results, and closing surveys via natural language.

Validates startup ideas with a deterministic scorecard, evidence brief, and verdict before code is written, integrating with MCP-aware build agents to avoid building dead-on-arrival products.

Enables natural language control of OmniPlan 4 on macOS, allowing creation and manipulation of tasks, resources, dependencies, and project metadata through MCP-compatible agents.

Prioritizes tasks by eliminating distractions, returning a ranked shortlist based on a given goal.

Official MCP server for FeatureJet, enabling agents to read and act on customer feedback boards: list/search posts, file feature requests, and pull top-voted planned items.

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

An A/B experiment runner for the A2A network that provides deterministic sticky bucket assignment, conversion recording, and two-proportion Z-test statistical significance calculation, with pay-per-call pricing via x402 on Base USDC.

A task-management MCP server that enforces strict gates on task states, WIP limits, and closing reasons, refusing operations that would leave the list ambiguous or rotting.

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.

Enables an AI agent to audit a website for launch readiness, find suitable startup/SaaS/AI directories using filters like DR and link type, and submit product listings to SaaSCity as drafts.

An MCP server that provides a drag-and-drop UI for prioritizing list items, allowing users to reorder items interactively and send the prioritized list back to the chat. It supports MCP Apps UI rendering and falls back to text instructions for hosts without UI support.

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.

It exposes a public, authenticated, allowlisted MCP surface for AgentSam Brand and Campaign capabilities, enabling compatible hosts to retrieve brand context, inspect assets, draft and evaluate brand/campaign artifacts, rank concepts, plan, and save authorized records while avoiding private operator control-plane access.

Enables AI agents to report and vote on infrastructure needs, providing developers with ranked demand signals to prioritize what to build next.

Enables conversion of business briefs or authenticated saved projects into structured handoffs for the Lovable plugin, with both anonymous basic mode and authenticated full mode including knowledge base, SEO, WCAG, security, and roadmap guidance.

Enables AI agents to collect, retrieve, and manage feedback on static HTML mockups through 9 MCP tools, with support for local or remote data and stdio/HTTP transports.

Enables LLM clients to answer prospect questions about Timers Studio, a professional broadcast timer platform, with first-party data on competitive positioning, use cases, personas, and recommended plans.