Image: Manifold
Why it mattersTeams running SEO or marketing work through an agent can now swap several per-tool scrapers and keys for one MCP endpoint, so the cost of adding a new data source becomes a credit charge instead of a build.
SEO work from inside an AI agent still means ten separate tools and ten API keys for most teams, and a new hosted MCP server tries to replace the ten with one. Manifold, launched on Product Hunt on 11 October, is a single URL that an agent calls over the Model Context Protocol for SEO rankings, a user's own Search Console and Google Analytics data, chatbot citation checks on ChatGPT, Claude and Gemini, verified business contact search, competitor ad libraries, and seven social platforms. The launch sits at 119 upvotes, with the maker, Jesse Sibley, saying he built and ships it solo.
The site lists twelve tool categories. Four are the obvious marketing data: SEO rankings and backlinks, the user's own Google and Bing Search Console numbers, Google Analytics sessions and conversions, and a people-and-companies lookup with verified work emails. Three are AI-answer specific: whether ChatGPT, Claude and Gemini name the user's product, how often they do, and which pages they cite. The rest are competitor ad libraries, Reddit, TikTok, Instagram, Facebook, YouTube, LinkedIn and X.
How an agent connects
Any client that supports a remote MCP server connects at https://mcp.manifoldmcp.com/mcp with an OAuth sign-in or a bearer API key. The site names Claude, ChatGPT, Cursor, Claude Code, Codex, Gemini CLI, Grok and OpenCode as working clients, and says any other remote-MCP client will work. One of the comments on the Product Hunt launch is from someone adapting it in Cursor.
Pricing
Manifold uses credits. A new workspace starts with 250 free credits and no card. Paid plans begin at $20 a month for 2,500 credits on the Pro plan, with a Max plan at a lower rate per credit, and a $10 top-up option between renewals. The site says each tool shows its credit cost before an agent runs it, so an agent can be instructed to stop a call that costs more than a chosen number. Per-call credit prices are not published.
One stated limit
Sibley says in the Product Hunt discussion that the AI chatbot recommendation check runs single-shot today, so a chatbot's output on one run is one sample rather than a measure of citation frequency across many runs. A team that cares about citation rate rather than a single answer should run the check more than once, by hand or on a schedule, and compare the results. Sibley also lists an MIT-licensed skills library of pre-built workflows for anyone who wants to call Manifold from a custom agent.
The pitch is that an SEO or marketing team working through Claude Code or a Cursor agent today has to wire the same ten APIs together on its own. For that team, one MCP endpoint, one bill and one audit log replace ten builds. The limit of the pitch is the single-shot citation check and the fact that Manifold is a hosted service, so queries about a client site run through a third party.
Source
This item was written by an AI system from the linked source. Reveneau is responsible for what it publishes.
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