"A server for finding coding resources and programming information" matching MCP servers:

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables discovery of a company's public feature board (Canny, Featurebase, Frill, UserVoice, Productboard) from its domain and retrieval of its most-voted requests with votes, status, comments, and the integrations customers ask for. Supports monitoring runs that surface only new requests, status changes, and vote jumps since a prior run using a saved state key.

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 agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.

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.

Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.

A Model Context Protocol server that provides Monte Carlo forecasting tools for project duration, cost, completion dates, and sensitivity analysis using three-point estimates and historical throughput.

Enables AI agents and coding assistants to access live Steam market intelligence, including app search, store details, player-count trends, review mining, and news digests.

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

Deterministic marketing math for AI agents: 62 engines that compute LTV:CAC, CAC payback, pipeline coverage, A/B test significance, budget allocation, pricing and retention from your own numbers. Runs locally with Node 18+, makes no network calls and stores no data.

Decision memory for teams building with AI coding agents. Captures every engineering decision once, ranks it by blast radius, and briefs every MCP-compatible agent before it acts, so agents stop making conflicting changes across repos.

Enables traceable requirement discovery, technical alignment, and ISO-aligned process checking through deterministic MCP tools and resources, without requiring an embedded LLM.

Enables coding agents to read feedback left on a running app—including the thread, page, pointed-at element, and screenshots—and to report back, manage feedback items, and publish review links.

Enables a coding agent to keep one JSON feature specification per feature, governed by a progressive schema, and to render it as editable Markdown documents for a product owner. Answers and direct Markdown edits are reconciled back into the validated model through stdio MCP tools, applying coherent changes and reporting those that widen scope or contradict the model.

Prevents premature AI coding by transforming vague product ideas into structured specifications, architecture decisions, and acceptance criteria through a series of interrogation and compilation tools.

A hypothesis-driven B2B positioning engine with 8 tools for strategic positioning, competitive analysis, and go-to-market messaging.

An opinionated MCP server for App Store Connect that provides 13 curated tools, slash-command workflows, and a Claude Skill to manage apps, reviews, sales, and pre-submission audits via natural language.

Enables coding agents to generate software engineering documents — PRD, SRS, ERD, SDD, design spec, traceability matrix, and agent instructions — as Markdown so they build from written specifications instead of guessing. Unsupplied inputs are marked [NOT SUPPLIED] or UNMAPPED rather than filled with invented data.

Enables agents to create and drive instrumented Design Thinking sessions, inspect the append-only journal, and retrieve dossiers and handoff specs through MCP tools and resources.

Enables coordinating multiple AI coding sessions by tracking features, decisions, and approval gates in a per-project Postgres database, with atomic IDs and commit-stamped append-only history.