Pipepost vs ProductClank
A side-by-side look at the Pipepost and ProductClank MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Pipepost for marketing work as a local process; choose ProductClank for marketing over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Pipepost when
- You need dedicated capabilities in the Marketing domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: other.
- You want tools like
seo_score, seo_meta, seo_schema.
Choose ProductClank when
- You need dedicated capabilities in the Marketing domain.
- You prefer a remote HTTP/SSE transport.
- You want tools like
search_products, create_product, check_balance.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Marketing | Marketing |
| Quality signal | 60/100 · Good | 60/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Remote HTTP/SSE |
| Auth | other | Not declared |
| Pricing | Freemium | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 5 | 11 |
| Directory activity | 4 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 29 | 54 |
| Full listing | View Pipepost | View ProductClank |
Tools & capabilities
Pipepost tools 29
seo_scoreAnalyze markdown content for SEO quality and return a 0-100 score with grade. Basic scoring (heading structure, word count, keyword density, readability) requires no credentials and is FREE. Full analysis (issue list, prioritized suggestions, related-keyword gaps) costs 1 credit. Returns: { score, grade, breakdown, issues?, suggestions? }. Common errors: missing 'content' (VALIDATION_ERROR), insufficient credits for full analysis (PAYMENT_REQUIRED).seo_metaGenerate SEO-optimized meta title (<60 chars), meta description (<160 chars), and Open Graph tags from article content. No external API calls; runs locally. Costs 1 credit per call. Returns: { title, description, og: { title, description, image_alt }, twitter: { card, title, description } }. Common errors: insufficient credits (PAYMENT_REQUIRED).seo_schemaGenerate valid JSON-LD structured data for Schema.org Article, FAQPage, or HowTo types. Output is ready to paste into a <script type="application/ld+json"> tag. Costs 1 credit per call. Returns: { jsonld: string, type: 'Article'|'FAQPage'|'HowTo' }. Common errors: invalid type for the supplied content shape (VALIDATION_ERROR), insufficient credits (PAYMENT_REQUIRED).index_nowSubmit one or more URLs to the IndexNow API for instant search-engine indexing across Bing, Yandex, Naver, and Seznam (Google does not participate in IndexNow). FREE. No platform credentials required; uses the Pipepost shared key. Returns: { submitted: number, key, accepted: string[], rejected: string[] }. Common errors: malformed URL or non-https scheme (VALIDATION_ERROR), upstream 4xx from IndexNow (PLATFORM_ERROR).cover_imageSearch Unsplash for cover images. FREE. Requires Unsplash access_key via setup. Subject to Unsplash's 50 req/h demo or 5000 req/h production rate limit. Returns: { results: [{ url_full, url_regular, url_small, photographer, photographer_url, attribution_html, alt }] }. Common errors: missing Unsplash key (VALIDATION_ERROR), rate-limit exceeded (PLATFORM_ERROR).publishPublish a markdown article to one CMS platform: devto, ghost, hashnode, wordpress, medium, or substack. Costs 1 credit per call. Requires platform credentials configured via the 'setup' tool. Supports draft|published status, tags, canonical_url, series, and cover image. Substack is published via reverse-engineered cookie auth. Returns: { url, id, platform, status }. Common errors: platform not configured (VALIDATION_ERROR), credit exhaustion (PAYMENT_REQUIRED), upstream 4xx/5xx (PLATFORM_ERROR), network timeout (NETWORK_ERROR).list_postsList your published and draft posts on a configured platform (devto, ghost, hashnode, wordpress, medium, substack). FREE. Requires platform credentials. Returns: { posts: [{ id, title, status, url, published_at }] }. Common errors: platform not configured (VALIDATION_ERROR), upstream auth failure (PLATFORM_ERROR).cross_publishPublish one article to multiple CMS platforms in a single call. Costs 1 credit total regardless of how many platforms (typical use: 5 platforms). The first successful platform's URL is wired as the canonical for the rest. Requires credentials for every target platform. Returns: { results: [{ platform, status: 'success'|'error', url?, error? }], canonical_url, summary: { ok, failed } }. Common errors: zero platforms configured (VALIDATION_ERROR), credit exhaustion (PAYMENT_REQUIRED). Per-platform failures are reported in results without aborting the whole call.frontmatterGenerate correctly-formatted frontmatter for SSGs and publishing platforms: hugo, jekyll, astro, nextjs, devto, hashnode, ghost. FREE. Auto-extracts description, reading_time, slug, and suggests tags from content. No external calls. Returns: { frontmatter: string, format, extracted: { slug, reading_time_min, description } }. Common errors: unknown format (VALIDATION_ERROR).generate_social_postsGenerate platform-optimized social copy from an article: twitter (thread), linkedin (long form), reddit (post + suggested subreddits), bluesky (single post within 300 graphemes). Costs 1 credit per call regardless of platform count. No platform credentials required (this generates copy; use bluesky_post / linkedin_post / x_post / mastodon_post to actually post). Returns: { posts: { twitter?, linkedin?, reddit?, bluesky? } }. Common errors: insufficient credits (PAYMENT_REQUIRED).repurposeTransform a full blog post into platform-native content for twitter, linkedin, reddit, hackernews (title only), bluesky, newsletter (intro paragraph). Costs 1 credit per call. Output preserves URLs and respects each platform's character limits. Returns: { outputs: { twitter?: string[], linkedin?: string, reddit?: { title, body, subreddits }, hackernews?: string, bluesky?: string, newsletter?: string } }. Common errors: insufficient credits (PAYMENT_REQUIRED).analyticsFetch post views, reactions, and comments from every configured CMS platform (devto, ghost, hashnode, wordpress) and aggregate the totals. FREE. Requires platform credentials. Medium and Substack are listed but their APIs do not expose post-level analytics. Returns: { platforms: [{ platform, posts: [{ title, url, views?, reactions?, comments?, published_at? }], note? }], summary: { total_posts, total_views, total_reactions } }. Common errors: no platforms configured (VALIDATION_ERROR), upstream auth failure surfaces per-platform in 'note'.- +17 more on the listing page
ProductClank tools 54
search_productsSearch the user's ProductClank products by name and return their IDs. A product_id is required to create or boost a campaign — use this to resolve it, then confirm the match with the user.create_productList a new product on ProductClank as a token-free listing (no crypto/token, no wallet). At minimum pass a `url` — the server auto-fills the name, tagline, description, logo, and X handle from the site; any field you pass explicitly overrides what's extracted. Socials are optional. Use this when search_products finds no existing match and the user wants to run a boost or campaign for a product that isn't listed yet. Returns the new product's id (and reuses an existing listing if one already matches, rather than duplicating). FREE — no credits charged. Confirm the product details with the user before calling.check_balanceReturn the connected user's ProductClank credit balance and plan. Use before launching a campaign to confirm they have enough credits (a content campaign costs 1000; a reply or quote-post boost 200; likes/bookmarks/reposts 300; a discovery campaign 10 to create + 12/post discovered).credit_historyThe connected user's credit transactions (purchases, campaign spend, participation rewards), newest first. Free, read-only. Use to account for what this connector has spent or earned. Top-ups are NOT available in-connector — send the user to app.productclank.com/credits/purchase when the balance runs low.boost_postRally the ProductClank community to engage with a specific social post. Creates a boost campaign and spends the user's credits: 'replies' generates AI reply drafts and 'quote' generates AI-drafted QUOTE POSTS (a repost WITH each member's own text, shown above the quoted post in their followers' feeds, the highest-reach action) — both cost 20 credits per draft, 10 drafts (200 credits) by default; set `count` (1–10) for a smaller boost, e.g. 3 replies = 60 credits. 'likes' (30 likes), 'bookmarks' (10 bookmarks — saving a post on X lifts its visibility) and 'repost' (10 reposts) cost 300 and ignore `count`. Supports Twitter/X, Instagram, TikTok, LinkedIn, Reddit, Farcaster, and YouTube (replies + likes on YouTube; reposts only on X and Farcaster; quote posts and bookmarks only on X) — the platform is auto-detected from the URL. product_id is OPTIONAL: link a product (from search_products or create_product) to tailor replies with the product name, or omit it for a tweet-first boost that uses generic amplification language. A TikTok video under ~1 minute old has no caption yet: the boost is still created, drafts are generated once TikTok publishes the caption (usually within a few minutes), and credits are charged only then — the result says waiting_for_post_text. Pass post_text if you already know the caption to skip the wait. Delivery is immediate by default; to pace it (e.g. 'reply 3 times over the next 6 hours'), set spread_over_hours — one slot goes out now and the rest drip out 1–2 an hour so the last lands within that window, at the same price. On a TikTok / YouTube / Instagram Reel VIDEO, add watch_quiz for 'Watch & answer': viewers can also watch to the end and answer one counting question (a linked 24h watch quiz, billed 100 credits per correct answer on top of the boost price, up to max_answers — see create_watch_quiz). Confirm the action and its credit cost with the user before calling.create_watch_quizGet people to watch a video ALL the way through: viewers open it, wait its full length, then answer ONE counting question about it ('how many times does she say X?') that only a viewer can answer. A right answer earns ProductClank points; a wrong first answer gets one more try (watch again). Public, runs exactly 24 hours. Works on any video link (TikTok, YouTube, Instagram Reels, …). COST: nothing now — the user pays 100 credits per CORRECT answer (wrong answers are free) for 24 hours after this chat, for at most max_answers people (default 20 = 2,000 credits max). Needs 100 credits on hand. Before calling: get the questions AND answers from the user (or run suggest_quiz_questions and have them confirm), and confirm max_answers and the maximum spend. Note for the user: paid watch time may count as artificial engagement under the platform's rules. To add a quiz to a boost of the same video, use boost_post's watch_quiz instead.suggest_quiz_questionsAI watches a TikTok (frames + captions) and suggests counting questions with their answers and the evidence for each — high confidence only. Creates nothing. Costs 40 credits, charged only when questions come back. Show every question WITH its evidence to the user and pass only the ones they confirm to create_watch_quiz (or boost_post's watch_quiz). If it fails, nothing is charged — ask the user for questions instead.get_watch_quiz_resultsResults of one of the user's watch quizzes (made here, in the web app, or on a boost): state (live / paused / ended), how many people started, answered, got it right, ran out of tries, or used their second try, how each question did, and the credits billed so far. Free, read-only. A question most viewers miss is usually ambiguous — say so. 'paused' with credits left means the user paused it; otherwise the balance ran out.launch_tiktok_campaignOne call for a full TikTok push on ONE video: 30 community likes + up to 10 community replies (AI-drafted comments) + a 24h 'Watch & answer' quiz (viewers watch to the end and answer a counting question). Use it when the user asks for a 'full', 'full blown', 'complete' or 'combo' TikTok campaign, or for likes + replies + quiz together, instead of calling boost_post and create_watch_quiz one by one. Defaults: likes on, 10 replies, quiz for 10 correct answers. Price: likes 300 credits, replies 20 credits each (10 = 200), billed up front; the quiz bills 100 credits per CORRECT answer over 24h, up to quiz_answers (10 = up to 1,000). FLOW: (1) call WITHOUT confirmed to get the free plan and show the user the steps and credit totals; (2) after the user says yes, call again with confirmed: true. If quiz_questions are missing on the confirmed call, the tool suggests questions from the video (40 credits) and creates nothing yet: show the user each question with its evidence, let them fix the answers, then call a third time with quiz_questions and confirmed: true. Each campaign bills separately; on a partial failure the result lists what was created — never call again blindly, it would create duplicates.suggest_content_campaignPreview a content campaign for a product BEFORE launching it. FREE — nothing is created and no credits are charged. Returns an AI-drafted campaign (title, description, call-to-action) plus whether the user can afford to launch it (1000 credits). Show the user the draft AND the credit cost, get an explicit yes, then call create_content_campaign — never launch off the back of the preview alone. Requires a product_id from search_products; write the campaign_message brief from what you know about the product.create_content_campaignLaunch a content campaign: rally the ProductClank community to create content (posts, threads, videos) for a product. Spends 1000 credits. The platform's AI expands your brief into a full campaign and auto-activates it; community submissions and winner selection happen in the ProductClank web app. Requires a product_id from search_products. Preview with suggest_content_campaign and confirm the 1000-credit cost with the user before calling.get_content_campaign_resultsSee what a content campaign actually produced: how many people submitted, the LIVE links to the content they published, which submissions were approved or rejected, and any winners picked. Free and read-only — safe to poll. This is how you close the loop on create_content_campaign; without it you only know a campaign was paid for, not whether it worked. Right after launch expect state 'processing' (the AI brief is still generating) and zero submissions — that is normal, not a failure. Accepts the campaign UUID or its public campaign number.- +42 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Pipepost
{
"mcpServers": {
"mendlem-pipepost": {
"command": "npx",
"args": [
"-y",
"pipepost-mcp"
]
}
}
}
ProductClank
{
"mcpServers": {
"productclank": {
"url": "https://mcp.productclank.com/mcp"
}
}
}
Frequently asked questions
Pipepost is categorized under Marketing and uses a local stdio subprocess. ProductClank belongs to Marketing and uses a remote HTTP/SSE transport. Pick Pipepost for marketing work and ProductClank for marketing.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Pipepost is listed as freemium — a free tier with paid plans. Auth: other. ProductClank has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add mendlem-pipepost and productclank as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Pipepost has a quality signal of 60/100 (Good) with 4 views, 0 installs and 5 GitHub stars. ProductClank has 60/100 (Good) with 1 views, 0 installs and 11 GitHub stars.