This practical produces the three competitor lists from Lesson 4.2 by asking Claude, connected to DataForSEO through its official MCP server. The calls are the same ones the lesson makes, so the analysis costs the same few cents; what Claude adds is finding the endpoint, making the request and turning the response into a table.
What this lesson covers
- Two ways to connect DataForSEO to Claude
- Rules that keep every API call visible and capped
- Ranking-keyword overlap as a classification signal
- Aspirational competitors from a fixed query list
- AI-citation sources from the LLM Mentions endpoint
- Evidence and repeatability
DataForSEO’s MCP server gives Claude four tools: three that read the API documentation and one that makes the request. The lesson connects it either as a remote connector you sign in to, or as a local server whose credentials sit in a configuration file, and explains why the first is safer. Before any data is requested, a short set of rules goes into the conversation: name the endpoint and parameters and wait for approval, report the cost field after every response, stop at a spending cap, and never estimate a number that is not in the data.
The three lists then follow the lesson’s method. Current-state competitors come from the competitors endpoint in DataForSEO Labs, sorted by shared ranking keywords rather than by any authority metric — on the demo site, that put developer and research sites at the top, which is a classification finding rather than a list of rivals. Aspirational competitors come from the SERP competitors endpoint across a fixed list of target queries, and the overlap between the two lists is where the gap matrix should be built. AI-citation competitors come from the LLM Mentions endpoint, with its limits stated: ChatGPT data covers US English only, and a mention in an AI answer is not a ranking.
Every table carries the endpoint, parameters, date and cost, so the same analysis can be repeated next quarter and compared like for like.
This practical continues Module 4, Competitive Entity Research & Gap Analysis, in The AI-powered Entity Audit, and produces the input for the Entity Gap Matrix in Lesson 4.4. It suits learners with a DataForSEO account who want competitor research that is fast, cheap and auditable.