"Information on MCP-Codex-Keeper" matching MCP servers:

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.

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.

Read Layerdock website feedback in your coding agent. Each pin comes with the CSS selector, screenshot, page URL and the console and network trace captured when the client reported it. Fix the bug, reply on the thread and mark it resolved without leaving the editor. Works with Claude Code, Cursor, Codex CLI, Windsurf, VS Code, Zed and Antigravity.

Enables AI assistants such as Claude, Cursor, and Codex to pull structured, source-backed, dated competitive intelligence — positioning, pricing, ads, social, reviews, hiring, momentum, and exploitable weaknesses — for any company in the universe, alongside the user's own projects, reports, battlecards, timelines, and evidence. Read-only by default, with optional opt-in competitor creation and plan-gated tools for deeper analysis.

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.

Provides adaptive question cards and guided multi-round interviews inside Codex, letting users clarify requirements one decision at a time and automatically sending chosen answers into the conversation.

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.

It enables AI agents to call human reviewers for second opinions and human judgment on artifacts such as designs, wording, and videos, then iterate using pinned feedback until the work is approved.

Enables AI assistants to conduct research, plan projects, generate PRDs, user stories and task lists, scaffold full-stack starter kits, map codebases, curate context, and execute multi-step development workflows.

Enables transforming grounded AI answers into interactive information views such as comparisons, plans, checklists, timelines, and decision views, while preserving a plain-language fallback.

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.

Enables AI assistants to perform software development tasks such as codebase analysis, research, planning, requirements and user-story generation, task management, project scaffolding, and multi-step workflow execution. It integrates with MCP-compatible clients like Claude Desktop, Cursor, and Cline AI.

Remote MCP server that lets AI assistants read tracked competitive intelligence — competitor news, reviews, website changes, social posts and ads — and act on it by managing projects, competitors, battle cards, reports and canvases. Every answer carries a source and a date, and write actions only publish when explicitly shared.

Enables Claude Code to query a trained sentiment model and Amazon Electronics review analytics through typed, read-only tools. Supports sentiment classification, statistics, keyword and similar-review search, product summaries and comparisons, negative aspect analysis, and model information.

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.

Connects Claude Code, Codex, Cursor, and other coding agents to a project's idea, feature topology, and ordered task queue over MCP, so they can answer planning jobs, claim, build, and tick off implementation tasks live in your repository, or assemble a shareable PRD.