Agent skill

SEO API

by seranking in seranking/seo-skills

SE Ranking API integration architect. An agent skill from seranking/seo-skills.

MITAuto-check passedMarketing & SEO

Install SEO API

skills CLI
$ npx skills add seranking/seo-skills --skill seo-api -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seranking/seo-skills seo-api --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/seranking/seo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-api .claude/skills/seo-api && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-api
GitHub stars
160
Token cost
~4.1k tokens
SKILL.md length
1,534 words
Files
5 (incl. references)
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

SE Ranking API integration architect. An agent skill from seranking/seo-skills.

  • Works in 8 steps: Preflight. → Clarify the goal. Ask 1–3 questions only… → Identify the API surface(s). Map the… → …
  • The user asks how to use the SE Ranking API
  • SKILL.md covers Prerequisites, Process, Output format and Tips, plus 2 more sections
  • Calls npx; reaches api.seranking.com and online.seranking.com; needs API_TOKEN

What it does

SEO API is an agent skill from seranking/seo-skills. SE Ranking API integration architect. Covers the whole SE Ranking surface — the Data API (keyword research, backlinks, domain & competitor analysis, SERP, website audit, AI Search) and the Project API (rank tracking, project/keyword/backlink management, marketing plan, sub-accounts, AIRT prompts). Answers any "how do I…" question about endpoints, parameters, JSON schemas, credit cost, rate limits, or auth, and produces ready-to-paste cURL / Python / TypeScript / MCP-tool-call recipes. With explicit confirmation…

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/api-surface-map.md`, `references/auth-and-keys.md` and `references/integration-patterns.md`).

It sits in Marketing & SEO, covering Link building, MCP servers and Third-party API integration. It works with Python, Model Context Protocol, TypeScript and Postman. The repository describes itself as: Claude SEO Skills — production Claude Agent Skills for the SE Ranking MCP server. Content briefs, AI Search share of voice, audits, backlink gaps, keyword clusters, schema… The licence is MIT.

When your agent uses it

  • The user asks how to use the SE Ranking API
  • Which endpoint returns a metric
  • How to build a rank tracker
  • For Postman / cURL / Python recipes

Example prompts

  • “how do I…”
  • “/seo-api”

Requirements

  • Python 3
  • A credential in API_TOKEN

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Preflight.
  2. Clarify the goal. Ask 1–3 questions only if the goal is ambiguous. Skip when the user already spelled it out. Useful follow-ups
  3. Identify the API surface(s). Map the goal to one or both of
  4. Map to tools / endpoints. For every step in the integration, name
  5. Forecast cost. Sum credit cost across all Data API calls. For Project API calls, surface plan-limit impact (e.g., "this consumes 1 Site +…
  6. Pick execution mode. Confirm with the user explicitly
  7. Execute or emit.
  8. Synthesise RECIPE.md. Always written, regardless of mode. The deliverable a developer reads to understand what was built or how to build…

What it can do on your machine

Read from SKILL.md and the folder at commit fd6d140. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.seranking.com
    • online.seranking.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • API_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO API loads about 4.1k tokens when it runs, and up to ~15k if it reads all its reference files. Until then it costs about 252 tokens; SKILL.md has 1,534 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~252
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~15k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from seranking/seo-skills at commit fd6d140, republished under its MIT licence (© seranking). 1,534 words, ~4,131 tokens.

Download SKILL.mdSave it as .claude/skills/seo-api/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
seo-api
description
SE Ranking API integration architect. Covers the whole SE Ranking surface — the Data API (keyword research, backlinks, domain & competitor analysis, SERP, website audit, AI Search) and the Project API (rank tracking, project/keyword/backlink management, marketing plan, sub-accounts, AIRT prompts). Answers any "how do I…" question about endpoints, parameters, JSON schemas, credit cost, rate limits, or auth, and produces ready-to-paste cURL / Python / TypeScript / MCP-tool-call recipes. With explicit confirmation it also wires up Project API state — creating projects, adding keywords, configuring audits, setting up AIRT prompt groups. Pulls live tool schemas from the connected MCP. Unlike the analysis skills (briefs, audits, reports), seo-api produces integration recipes and wired-up state. Use when the user asks how to use the SE Ranking API, which endpoint returns a metric, how to build a rank tracker, for Postman / cURL / Python recipes, or how to integrate with Looker / n8n / Make.

Live with the SE Ranking MCP at https://api.seranking.com/mcp. Tool schemas are introspected live; this skill never relies on a frozen snapshot of the API surface.

SE Ranking API Integration Architect

Help developers ship real integrations against the SE Ranking SEO Data API and Project API. The deliverable is either a code recipe (ready-to-paste cURL / Python / TypeScript / MCP-tool-call sequence) or live wiring of Project API state (create projects, add keywords, configure audits, set up AIRT prompts), or both. The skill knows the entire 195-tool surface, the credit and rate-limit cost of every call, and the canonical setup story for every major MCP client.

Prerequisites

  • SE Ranking MCP connected at https://api.seranking.com/mcp. Single API key authenticates both DATA_* and PROJECT_* tools through the unified gateway. If /mcp doesn't show se-ranking, the skill emits the install command and stops — see references/auth-and-keys.md.
  • (Optional) WebFetch for fetching deep guides at seranking.com/api/data/* and seranking.com/api/project/* when the request needs prose beyond JSON Schema.
  • User provides: an integration goal in plain language (e.g., "build a rank tracker for client X", "pull all backlinks for these 50 domains into BigQuery weekly", "configure an audit + AIRT prompts for a new project"). The skill interviews only when the goal is ambiguous.

Process

  1. Preflight.

    • Confirm the SE Ranking MCP is reachable. If not, emit:
      bash
      claude mcp add --transport http se-ranking https://api.seranking.com/mcp
      and stop. See references/auth-and-keys.md for OAuth vs. X-Api-Key header tradeoffs and headless / CI patterns.
    • Call DATA_getSubscription (0 credits). Record units_left, plan status, expiration — units_left is the figure to forecast against, and it gets printed in the cost forecast in step 5. Optionally also call DATA_getCreditBalance for its { limit, used } view — but the two are not aliases: they report different remaining-credit numbers that do not reconcile (an ~8.6M gap is normal), so treat getSubscription.units_left as the source of truth.
  2. Clarify the goal. Ask 1–3 questions only if the goal is ambiguous. Skip when the user already spelled it out. Useful follow-ups:

    • "Is this a one-off run, a recurring job (daily/weekly), or a long-lived integration in your product?"
    • "Target country / language / device — or worldwide?"
    • "Are we operating on a project you already own in SE Ranking, or just researching domains?"
  3. Identify the API surface(s). Map the goal to one or both of:

    • Data API — research-shaped data on any domain, no prior account setup. Credit-billed. See references/api-surface-map.md § "Data API surfaces".
    • Project API — operations on the user's own SE Ranking projects (rank tracking, audits, AIRT, backlink groups, marketing plan, sub-accounts). Subscription-limit-billed, not credit-billed. Requires Business or Enterprise plan. See references/api-surface-map.md § "Project API surfaces".
    • Many real integrations span both — e.g., a rank-tracker setup uses PROJECT_createProject + PROJECT_addKeywords + PROJECT_runPositionCheck, then reports use DATA_getDomainKeywords for the same domain.
  4. Map to tools / endpoints. For every step in the integration, name:

    • The MCP tool: `DATA_getDomainKeywords` or `PROJECT_addKeywords`.
    • The underlying REST endpoint + HTTP verb (e.g., GET /v1/domain/keywords).
    • The credit cost (Data API) or limit consumed (Project API). Source costs from references/rate-limits-and-credits.md and the per-endpoint pages at seranking.com/api/data/* — MCP tool description fields carry input schemas and usage notes but not credit costs.
    • If a tool needs an ID the user didn't supply (project ID, search engine ID, geo region name, language code), insert the prerequisite *list* or *available* call before it. See references/api-surface-map.md § "ID resolution".
  5. Forecast cost. Sum credit cost across all Data API calls. For Project API calls, surface plan-limit impact (e.g., "this consumes 1 Site + 50 Keywords + ~500 Audit Pages from your plan"). Compare against:

    • units_left from step 1 — if insufficient, surface and stop with the upgrade link.
    • Plan limits if Project API tools are involved — PROJECT_getUserProfile returns current usage; flag if the integration would push a limit over.
  6. Pick execution mode. Confirm with the user explicitly:

    • Code mode — emit ready-to-paste cURL, Python (requests), TypeScript (fetch), and MCP-tool-call variants. The developer runs them. Default for read-only research, recurring jobs the user wants to own, and anything they want to deploy outside their Claude session.
    • Live mode — execute the integration step by step via MCP. Confirm every mutating call. Default for one-off Project API setup (new project, add keywords, configure audit, set up AIRT prompt group, etc.) where the user wants the state to exist by the end of this conversation.
    • Hybrid — wire up the one-time setup live, emit code for the recurring workload (e.g., "I created the project and added the 50 keywords for you; here's the daily-run Python script to pull positions and write them to BigQuery").
  7. Execute or emit.

    • Code mode — write code/curl.sh, code/python.py, code/typescript.ts, code/mcp-calls.md. Each file is a complete runnable example, not a fragment. Include error handling for 429 (rate limit) and 403 (insufficient credits). See references/integration-patterns.md for canonical pattern snippets.
    • Live mode — for each mutating call (PROJECT_create*, PROJECT_add*, PROJECT_delete*, PROJECT_update*, DATA_createStandardAudit, DATA_createAdvancedAudit, etc.), print a single-line confirmation:
      About to call PROJECT_createProject(domain="acme.com", name="ACME Inc — Rank Tracker", country="us").
      Consumes: 1 "Site" from your subscription. Proceed? [y/N]
      Wait for explicit y / yes. On anything else, fall back to code mode and emit the equivalent code instead of executing. Read-only calls (DATA_get*, DATA_list*, PROJECT_get*, PROJECT_list*) run without confirmation. Log every call to evidence/03-execution-log.md with timestamp, args, response status.
  8. Synthesise RECIPE.md. Always written, regardless of mode. The deliverable a developer reads to understand what was built or how to build it. See output format below.

Output format

Folder seo-api-{slug}-{YYYYMMDD}/ where {slug} is a kebab-case summary of the goal (e.g., acme-rank-tracker, bulk-backlinks-bigquery).

seo-api-{slug}-{YYYYMMDD}/
├── RECIPE.md                       (primary deliverable — what was built or how to build it)
├── code/
│   ├── curl.sh                     (cURL one-liners + multi-step bash)
│   ├── python.py                   (idiomatic requests-based script)
│   ├── typescript.ts               (fetch + zod-validated responses)
│   └── mcp-calls.md                (MCP-tool-call sequence — same workflow, agent-native)
└── evidence/
    ├── 01-preflight.md             (credit balance, subscription status, MCP connectivity check)
    ├── 02-cost-forecast.md         (per-call cost breakdown, plan-limit deltas, total)
    ├── 03-ids-resolved.md          (Project API / search-engine IDs, geo codes resolved upfront — omit if none needed)
    └── 04-execution-log.md         (every MCP call executed, with args + status — omit in pure code mode where nothing ran)

Top-level: RECIPE.md + code/. The evidence/ folder preserves the reasoning trail; auditors lean on 02-cost-forecast.md and the execution log. 03 and 04 are conditional — a run with no ID lookups and no executed calls (pure code-mode advice) ships just 01 + 02.

RECIPE.md follows this shape:

markdown
# {Integration Title}: {target}

> Run dated {YYYY-MM-DD} · Mode: {code | live | hybrid} · Total cost: {n} credits + {plan-limits consumed}

## Goal

{1–2 sentences. What was asked, what's being shipped.}

## API surface map

| Step | MCP tool | REST endpoint | Verb | Cost |
|------|----------|---------------|------|------|
| 1    | `DATA_getCreditBalance` | `/v1/account/subscription` | GET | 0 credits |
| 2    | `PROJECT_listProjects` | `/v1/account/projects` | GET | 0 (plan limit: read) |
| 3    | `PROJECT_createProject` | `/v1/projects` | POST | 1 Site from plan |
| ...  | ... | ... | ... | ... |

## Auth & setup

{cURL header / Python session / TypeScript fetch wrapper showing exactly how to authenticate. Reference `references/auth-and-keys.md` for OAuth vs. header tradeoffs.}

## Cost forecast

- Credit cost (Data API): {n} credits ({explanation per call})
- Plan-limit consumption (Project API): {Sites: n, Keywords: n, Audit Pages: n, AIRT Prompts: n}
- Your balance at run time: {units_left} credits, {plan limits available}
- {OK / WARNING: this integration would push X over plan limit}

## Recipe

### Option A — cURL

(complete bash script in `code/curl.sh`)

### Option B — Python

(complete script in `code/python.py`)

### Option C — TypeScript

(complete script in `code/typescript.ts`)

### Option D — MCP tool calls

(agent-native sequence in `code/mcp-calls.md` — for when this integration lives inside another Claude/Cursor/Codex workflow)

## Rate limit & retry strategy

- Data API: 10 RPS, Project API: 5 RPS. Pace sequentially for batched workflows; small-batch parallelism (≤3 concurrent) is safe.
- 429 handling: exponential backoff with jitter (1s → 2s → 4s → 8s, ±20% jitter). 5xx: same. Treat 403 "Insufficient funds" as terminal — no retry.

## What's running now (live mode only)

{Bullet list of MCP calls that were executed, with their outcomes. Pulled from `evidence/04-execution-log.md`.}

## What you still need to do

{Concrete next steps for the developer. E.g., "Run `python.py` daily via cron at 06:00 UTC", "Open the project at https://online.seranking.com/...", "Add a webhook for rank changes via Settings → Notifications".}

## Linked docs

- {Direct links to the relevant pages on `seranking.com/api/data/*` and `seranking.com/api/project/*`.}

## When to escalate to another skill

- `seo-content-brief` — once your integration is pulling keyword data, this skill turns it into editor briefs.
- `seo-technical-audit` — if the integration involves website audits, this skill interprets the audit output.
- `seo-drift baseline` — if the integration's job is to track a domain over time, snapshot it first.
Show full SKILL.md (602 more words)Show less

Tips

  • Single API key authenticates everything. API_TOKEN (or X-Api-Key header for headless) covers both DATA_* and PROJECT_*. The legacy split into separate Data and Project keys is gone — passing both still works as headers for backwards compatibility, but you can use just X-Api-Key now. See references/auth-and-keys.md.
  • Rate limits are per-API-key, not per-IP. All threads / workers / servers sharing one key contribute to the same 10-RPS (Data) or 5-RPS (Project) budget. For production fan-outs, mint multiple keys via the API Dashboard.
  • Failed requests are free. 4xx and 5xx never consume credits. Don't over-engineer cost protection for normal error retries.
  • Project API limits are not credits. They consume your subscription's "Sites", "Keywords", "Audit Pages", "AIRT Prompts" quotas. Surface plan-limit impact upfront for any mutating call — these limits are stickier than credits because the user has to upgrade their plan to lift them, not just buy a credit pack.
  • Confirm before mutating. PROJECT_create*, PROJECT_add*, PROJECT_delete*, PROJECT_update*, DATA_create*Audit, DATA_deleteAudit all permanently modify account state. Always print a one-line summary (tool, args, what gets consumed) and wait for y/yes before calling.
  • Use the right ID resolution tool. Most "I want to operate on project X / keyword Y" requests need an ID lookup first. See references/api-surface-map.md § "ID resolution" for the full table. Common cases:
    • Project IDs → PROJECT_listProjects (or PROJECT_listOwnedProjects / PROJECT_listSharedProjects for sub-account setups).
    • Search engine for rank tracking → pass country_code directly to PROJECT_addSearchEngine (ISO 3166-1 alpha-2). Only fall back to PROJECT_getAvailableSearchEngines for regional engines (Catalonia, Turkish-Cypriot Cyprus).
    • SERP locations → DATA_getSerpLocations.
    • Languages → PROJECT_getGoogleLanguages.
    • Regions for local rank tracking → PROJECT_getAvailableRegions (use the verbatim name field; abbreviations are rejected).
  • For exports, poll the status endpoint. Async endpoints (/backlinks/export, /keywords/export) return a task ID; subsequent polls of *ExportStatus count against the rate limit but cost 0 credits. Start with a 5s poll interval; exponential backoff if the task is large.
  • Check the MCP tool description before WebFetching docs. Every MCP tool exposes its full input schema, defaults, and usage notes via the protocol — e.g. DATA_getDomainCompetitors documents its own ~60KB response cap. One thing the descriptions do not carry: credit costs — for those, use references/rate-limits-and-credits.md and the public per-endpoint pages.
  • Large list endpoints can overflow the MCP transport. DATA_getDomainCompetitors on a popular domain — and DATA_getDomainKeywords / DATA_getAllBacklinks on big domains — return responses past the MCP client's inline token limit; the result is auto-saved to a file instead. Recover it with a jq slice on the saved file, or call the REST endpoint directly (raw REST has no size cap). See references/api-surface-map.md.
  • For "show me Swagger / OpenAPI for the MCP" — point the developer at MCP Inspector (npx @modelcontextprotocol/inspector https://api.seranking.com/mcp) or mcp-scan. Both walk the live tool/prompt/resource catalogue. A canonical MCP→OpenAPI converter is on the roadmap; for now the inspector output is the source of truth.

Works well with

  • Predecessors: none — entry point for any API integration question.
  • Successors (when the integration starts producing data):
    • seo-content-brief — when the integration pulls keyword research that should become editor briefs.
    • seo-page — when one URL from the integration needs a keep/refresh/consolidate/kill verdict.
    • seo-drift baseline — to snapshot a domain or URL before the integration starts running, so regressions are detectable.
    • seo-technical-audit — when the integration involves audit runs and the output needs prioritisation.
    • seo-ai-search-share-of-voice — when the integration tracks AIRT visibility and needs a competitive read.

References

  • references/auth-and-keys.md — API key formats, OAuth vs. header, headless / CI patterns, key rotation.
  • references/rate-limits-and-credits.md — 10 RPS / 5 RPS, credit billing models, plan-limit consumption, error codes (429, 403), exponential-backoff template.
  • references/api-surface-map.md — full routing table (which API owns what) + ID resolution table + decision tree for "which tool do I need".
  • references/integration-patterns.md — five canonical recipes copy-paste-ready: rank tracker setup, bulk backlink export, audit pipeline, AIRT visibility tracker, keyword research bulk job.

© seranking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/seo-api of seranking/seo-skills.

  • SKILL.md
  • references/api-surface-map.md
  • references/auth-and-keys.md
  • references/integration-patterns.md
  • references/rate-limits-and-credits.md

Open the folder on GitHubat commit fd6d140

Compare with similar skills

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Categories

Questions about SEO API

What does SEO API do?

SE Ranking API integration architect. An agent skill from seranking/seo-skills. SEO API is an agent skill from seranking/seo-skills. SE Ranking API integration architect.

When should I use SEO API?

SEO API fits situations like: the user asks how to use the SE Ranking API; which endpoint returns a metric; how to build a rank tracker; for Postman / cURL / Python recipes.

How do I install SEO API in Claude Code?

Run `npx skills add seranking/seo-skills --skill seo-api -a claude-code`. Or copy the skill folder (skills/seo-api in seranking/seo-skills) into .claude/skills/seo-api in your project. Claude Code loads it when a task matches its description.

How do I install SEO API in Codex?

Run `npx skills add seranking/seo-skills --skill seo-api -a codex`. Or copy the skill folder (skills/seo-api in seranking/seo-skills) into .agents/skills/seo-api in your project. Codex loads it when a task matches its description.

Can I use SEO API in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seranking/seo-skills --skill seo-api -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-api, .gemini/skills/seo-api, .github/skills/seo-api and .opencode/skills/seo-api in your project.

What does SEO API need to run?

Going by SKILL.md and its folder, SEO API needs the command-line tools its instructions call (npx) and credentials named API_TOKEN. Our summary lists: Python 3; A credential in API_TOKEN.

Does SEO API access the network?

SKILL.md names 2 domains. In commands or code: api.seranking.com and online.seranking.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is SEO API safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO API use?

SEO API is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO API use?

About 4.1k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.

What are the alternatives to SEO API?

Skills that share tags, products or a category with SEO API: SEO Dataforseo (hashgraph-online/awesome-codex-plugins, 1.2k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 787 stars), DataForSEO Live SEO Data (AgriciDaniel/claude-seo, 18k stars) and Sellersprite Amazon Research (liangdabiao/amazon-sorftime-research-MCP-skill, 940 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO API?

seranking (a GitHub organization) maintains it in seranking/seo-skills, which has 160 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 25, 2026.

Source: seranking/seo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.