Why the plan comes from your AI, not from Teddit
A generic tool can see that an assistant stopped naming you on a prompt. It cannot know that the page it used to cite was rewritten last month, that the product it describes is being retired, or that your team has no one to write comparison pages this quarter. Those facts decide what is worth doing, and they live with you.
So Teddit does not produce recommendations. It has an MCP server built in, which lets an AI client such as Claude, Cursor or another MCP client read every answer, source and number in your workspace. Your AI brings the context; Teddit brings the evidence. Reading costs nothing.
Connect it in five minutes
Create a key. In the app, click the gear icon in the top bar, open API & MCP and press Create key. Name it after where it will be used. Choose the access:
- Read for analysis and planning. This is all a planning session needs.
- Read + edit if you want your AI to add prompts or competitors, for example as drafts you approve.
- Read + scan only if it should run scans, which are paid from the workspace balance.
The key starts with tdt_ and is shown once. A key can never do more than the role of the person who created it.
Add the server to your client. The address is https://teddit.io/mcp and the key goes in the Authorization header. In Claude Code it is one command:
claude mcp add --transport http teddit https://teddit.io/mcp \ --header "Authorization: Bearer tdt_…"
Claude Desktop starts MCP servers as local programs, so it connects through a small open-source bridge, mcp-remote, which needs Node.js. Cursor and other clients that speak Streamable HTTP and can send a header connect directly. The exact configuration for each is on Connect the MCP server.
Check it. Ask: “Use Teddit and tell me which workspace you are connected to.” Your AI should call whoami and name the workspace and the key’s access.
A planning session, question by question
The order below goes from the overall picture to single answers, then to your own pages. Name the site in the first question; a workspace can hold several. The examples use Brightloop, the made-up email platform from our docs.
1. Where do we stand?
How did Brightloop do over the last four weeks? Give me the main numbers per assistant and say which prompts we gained and lost.
Your AI will use get_dashboard and get_trends. Ask it to separate prompts that held from prompts that flickered: get_trends sorts them into held, volatile and lost, and only the held and lost ones are worth planning around.
2. Where do competitors win?
List the prompts where a competitor is named and we are not. Group them by category and say which competitor appears most.
This is list_prompts with the verdict “lost” (competitors only). For one rival in depth, get_competitor_report gives the prompts where only they are named, both of you, or only you, and the pages of their site the assistants cite.
3. What are those answers built from?
For the five most important of those prompts, open each assistant’s answer. Which pages did they cite, and which web searches did they run?
get_prompt returns one assistant’s answer in full, with its sources in groups (your site, other people’s pages, competitors’ sites, reference) and the searches it ran. It returns one answer per call, so keep this step to a short list.
4. Which of our pages are missing?
Which pages of our site do the assistants link to now, and which of our guides and comparison pages are never linked?
list_pages with shown: "yes" and shown: "no". The second list is often the most useful one in the session.
Turning it into a plan
Now add what Teddit does not know. Paste or attach your positioning, your list of existing pages with their owners, your content calendar, the constraints you work under. Then ask for the plan with conditions attached:
Using what you found and the context I gave you, propose up to five changes for the next month. For each, name the prompts it is meant to move, the evidence from the answers, and what we should see in the scans if it works. Mark anything that is a guess.
Three habits make the result more trustworthy.
- Ask for evidence per item. A change that cannot point at specific answers and sources is an opinion. That can be fine, but you should know which it is.
- Ask what would disprove it. If a new comparison page is meant to get you named on three prompts, write those three down with the date the page went live.
- Keep the measurement separate. The scans stay on their schedule with the same prompts and the same models. Do not edit the prompts you are trying to move; add new ones beside them if you need to.
The two prompt templates on the server package parts of this. weekly_review asks your AI to review a site’s week: what moved, the likely reason, three actions and a chart. grow_prompt_set asks it to propose new questions for your weakest categories and add them as drafts once you agree. In both cases the review and the proposals are written by your AI from the data, not by Teddit.
Following up
A month later, run the same session with the list of changes in hand. Ask your AI to compare the prompts each change was meant to move, before and after, assistant by assistant, and to say plainly where nothing happened. A change that did not move the answers is a finding too.
If you want to check a few prompts sooner than the schedule, a key with Read + scan access can run a scan of selected prompts. It is a real scan, paid from the balance and counted against the site’s monthly cap. Ask for estimate_scan first. To read individual changes over weeks, see One scan is a sample; for more questions to ask, see the example questions and the tools reference.