What can you do with this server?

This server enables AI assistants to perform practical SEO research through the following capabilities: * Backlink Analysis: Retrieve backlinks for a domain (with title, URL, domain rating), get a full domain overview (rating, total backlinks, referring domains), and compare SEO metrics across 2–5 domains. * Keyword Research: Generate keyword and question ideas from a seed keyword (filterable by country and search engine), check keyword difficulty scores, and get SERP snapshots. * AI Search Queries: Generate AI-powered query ideas based on a keyword and specific search intents (informational, commercial, transactional, navigational). * Traffic Estimation: Estimate organic search traffic for a domain or URL, including historical data, top pages, top countries, and associated keywords. * Backlink Opportunities: Identify backlink sources used by competitors that are missing from a target domain's profile. * SEO Content Briefs: Create AI-assisted content briefs combining keyword difficulty, SERP analysis, AI search queries, and recommended content angles.

Which integrations are available for this server?

Provides SEO research capabilities including keyword difficulty analysis, keyword generation, traffic estimation, and backlink analysis using data from search engines.

How do I use SEO Research MCP?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@SEO Research MCP what are the backlinks for competitor.com?" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

de en es ja ko ru zh

SEO Research MCP

by egebese

Overview Schema Source Related Servers Discussions Admin

Python

Remote

DataSEO MCP

Give your AI assistant real SEO data. DataSEO MCP is a Model Context Protocol server that lets Claude, Cursor, and other MCP clients pull backlinks, keyword difficulty, traffic estimates, and keyword ideas from Ahrefs' free tools — plus optional AI query planning — just by asking in plain English.

No dashboards, no CSV exports. Ask "who links to suparank.io?" and get an answer inside your chat.

CAUTION

For educational and research use. It automates third-party services (Ahrefs, CapSolver, Anti-Captcha, OpenRouter). You are responsible for complying with their terms of service.

What you can ask

Talk to it in natural language — the assistant picks the right tool.

Ask something like…	Tool it uses	You get
"Who links to suparank.io?"	`get_backlinks_list`	Domain rating, referring domains, top backlink rows
"Give me keyword ideas for AI SEO tools"	`keyword_generator`	Keyword and question ideas
"How much organic traffic does suparank.io get?"	`get_traffic`	Monthly traffic, top pages, countries, keywords
"How hard is it to rank for 'AI SEO tools'?"	`keyword_difficulty`	KD score + the live SERP
"Generate AI search queries for 'AI SEO audit'"	`ai_search_queries`	Queries grouped by search intent
"Give me an SEO overview of suparank.io"	`domain_overview`	Backlink + traffic summary in one call
"Compare suparank.io with its competitors"	`compare_domains`	2–5 domains side by side
"Find backlink gaps for suparank.io"	`backlink_opportunities`	Sources linking to competitors but not you
"Write a content brief for 'AI SEO audit'"	`seo_content_brief`	SERP data + AI-assisted content angles

Maintained by Ege Bese. Built for the AI SEO and rank-tracking workflows behind Suparank.

Related MCP server: SEO Insights MCP Server

Quick start

Run it with no install using uv:

export CAPSOLVER_API_KEY="your-capsolver-key"
uvx --python 3.10 dataseo-mcp

That's enough to use every SEO tool. See MCP Setup to wire it into your assistant.

For local development:

git clone https://github.com/egebese/dataseo-mcp.git
cd dataseo-mcp
uv sync
uv run dataseo-mcp

The legacy seo-mcp command still works as an alias.

Configuration

One CAPTCHA provider is required — it's how the Ahrefs-backed tools clear the Turnstile challenge:

export CAPSOLVER_API_KEY="your-capsolver-key"
# or
export ANTICAPTCHA_API_KEY="your-anticaptcha-key"

If both are set, CapSolver is tried first and Anti-Captcha is the fallback.

AI tools are optional. ai_search_queries and seo_content_brief need OpenRouter; without it, the other tools still work and AI output is marked unavailable:

export OPENROUTER_API_KEY="your-openrouter-key"
export OPENROUTER_MODEL="openai/gpt-4o-mini"  # optional

Runtime overrides:

Variable	Default	Purpose
`DATASEO_CACHE_DIR`	`~/.cache/dataseo-mcp`	Signature cache location
`DATASEO_REQUEST_TIMEOUT`	`30`	HTTP timeout in seconds
`DATASEO_MAX_POLLING_ATTEMPTS`	`120`	CAPTCHA polling cap
`OPENROUTER_BASE_URL`	`https://openrouter.ai/api/v1`	OpenAI-compatible AI endpoint

MCP Setup

Claude Code:

claude mcp add dataseo --scope user -- uvx --python 3.10 dataseo-mcp

Claude Desktop / Cursor (claude_desktop_config.json or equivalent):

{
  "mcpServers": {
    "dataseo": {
      "command": "uvx",
      "args": ["--python", "3.10", "dataseo-mcp"],
      "env": {
        "CAPSOLVER_API_KEY": "YOUR_CAPSOLVER_KEY",
        "OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY"
      }
    }
  }
}

VS Code (.vscode/mcp.json):

{
  "servers": {
    "dataseo": {
      "command": "uvx",
      "args": ["--python", "3.10", "dataseo-mcp"],
      "env": { "CAPSOLVER_API_KEY": "YOUR_CAPSOLVER_KEY" }
    }
  }
}

Add OPENROUTER_API_KEY only if you want the AI tools.

API Reference

`get_backlinks_list(domain)`

{
  "overview": { "domainRating": 76, "backlinks": 1500, "refdomains": 300 },
  "backlinks": [
    {
      "anchor": "Suparank",
      "domainRating": 71,
      "title": "The best AI SEO tools",
      "urlFrom": "https://source.example/best-seo-tools",
      "urlTo": "https://suparank.io/",
      "edu": false,
      "gov": false
    }
  ]
}

`keyword_generator(keyword, country="us", search_engine="Google")`

Keyword and question ideas in the label / value shape. Volume and difficulty come back as Ahrefs' bucketed estimates.

`get_traffic(domain_or_url, country="None", mode="subdomains")`

Traffic history, traffic summary, and top pages / countries / keywords. Both costMonthlyAvg and the legacy costMontlyAvg spelling are included.

`keyword_difficulty(keyword, country="us")`

A keyword difficulty score plus the organic SERP rows with available metrics.

`ai_search_queries(keyword, count=10, model="openai/gpt-4o-mini", language="en")`

{
  "keyword": "ai seo audit",
  "queries": [
    { "query": "what is an AI SEO audit", "intent": "informational" },
    { "query": "best AI SEO audit tools", "intent": "commercial" }
  ],
  "model_used": "openai/gpt-4o-mini",
  "total_queries": 2
}

count is 1–50. Intents are informational, commercial, transactional, navigational.

Composite tools

domain_overview(domain, country="None") — backlink overview + traffic summary for one domain.
compare_domains(domains, country="None") — 2–5 unique domains side by side.
backlink_opportunities(domain, competitors) — competitor backlink sources missing from the target's sample.
seo_content_brief(keyword, country="us", count=12, model, language) — keyword difficulty, SERP rows, AI queries, and recommended content angles in one call.

How it works

server.py stays thin; the work is split into focused modules:

services.py — tool orchestration and public return shapes.
schemas.py — Pydantic validation and normalization.
captcha.py — CapSolver / Anti-Captcha fallback with bounded polling.
backlinks.py, keywords.py, traffic.py — Ahrefs endpoint adapters.
ai.py — OpenRouter query generation.
cache.py — JSON signature cache (default ~/.cache/dataseo-mcp).

Every external HTTP boundary is mocked in tests.

Development

uv sync
uv run pytest -q
uv run ruff check .
uv run python -m compileall -q src
uv run python -c "from seo_mcp.server import main"

Troubleshooting

Problem	Fix
No CAPTCHA provider configured	Set `CAPSOLVER_API_KEY` or `ANTICAPTCHA_API_KEY`
CAPTCHA solving failed	Check provider balance, key validity, and rate limits
AI tool returns a missing-key error	Set `OPENROUTER_API_KEY`
Empty SEO response	The domain or keyword may not be indexed upstream
`seo-mcp` command not documented	Use `dataseo-mcp`; `seo-mcp` still works as an alias

License

MIT with an educational-use notice. Original fork attribution is preserved in LICENSE.

Available Tools

4 tools

get_backlinks_listA

Get backlinks list for the specified domain
Args:
    domain (str): The domain to query
Returns:
    List of backlinks for the domain, containing title, URL, domain rating, etc.

ParametersJSON Schema

Name	Required	Description	Default
`domain`	Yes

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes return type and fields (title, URL, domain rating). No annotations provided, so description carries burden; it is transparent about the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise, all sentences contribute value. Front-loaded purpose with immediate clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter, the description covers purpose, input, and output sufficiently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage 0%; description adds 'The domain to query' which is minimal. Provides no additional context like format or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states verb and resource: 'Get backlinks list for the specified domain'. Distinguishes from sibling tools like get_traffic and keyword_difficulty.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit when-to-use or when-not-to-use. Implied usage for domain backlinks, but no guidance on alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_trafficC

Check the estimated search traffic for any website. 

Args:
    domain_or_url (str): The domain or URL to query
    country (str): The country to query, default is "None"
    mode (["subdomains", "exact"]): The mode to use for the query
Returns:
    Traffic data for the specified domain or URL

ParametersJSON Schema

Name	Required	Default
`domain_or_url`	Yes
`country`	No	None
`mode`	No	subdomains

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It does not disclose whether the tool is read-only, destructive, requires authentication, or has rate limits. For a data query tool, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at two sentences plus an Args/Returns list. It is front-loaded with the purpose and structured for easy scanning. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description only vaguely states 'Traffic data' without specifying structure. Combined with missing behavioral context, the description is incomplete for a 3-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description includes an Args section that lists parameters and their types, adding some meaning beyond the schema (e.g., domain_or_url is 'The domain or URL to query'). However, it does not explain the difference between 'subdomains' and 'exact' modes, nor the effect of the country parameter, beyond default values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Check the estimated search traffic for any website', which clearly identifies the verb and resource. It distinguishes from sibling tools like get_backlinks_list and keyword_difficulty by focusing on traffic estimation, but does not explicitly differentiate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, nor does it specify prerequisites or exclusions. It simply states the tool's function without context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

keyword_difficultyC

Get keyword difficulty for the specified keyword

ParametersJSON Schema

Name	Required	Description	Default
`keyword`	Yes
`country`	No		us

TDQS

C2.6/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must carry full burden. It does not disclose how difficulty is calculated, what unit/scale is used, or any side effects. Bare minimum.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence of 8 words is concise but lacks substance. Appropriate length for the content, but more detail would improve informativeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 2 params requiring explanation, the description is inadequate. Leaves agent guessing about return values, scope, and usage nuances.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage. Description only mentions 'specified keyword' without explaining its meaning or format. Country parameter and default are not explained. Adds minimal value to schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get keyword difficulty for the specified keyword' clearly states the action and resource. It is distinct from sibling tools like get_backlinks_list and get_traffic, though sibling differentiation is implicit rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool compared to alternatives. Lacks context about prerequisites or typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

keyword_generatorC

Get keyword ideas for the specified keyword

ParametersJSON Schema

Name	Required	Default
`keyword`	Yes
`country`	No	us
`search_engine`	No	Google

TDQS

C2.4/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. Description only says 'get ideas' with no disclosure of behavior (e.g., return format, rate limits, data source).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely short, no fluff, but lacks essential details. Conciseness is achieved at the expense of completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 3 parameters, no output schema, and no annotations, the description is severely incomplete. No information on return values or side effects.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and description only mentions the keyword parameter, ignoring country and search_engine. Fails to compensate for missing parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns keyword ideas for a given keyword. It distinguishes from sibling tools (backlinks, traffic, difficulty) but lacks specificity about the output format or scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs. alternatives, no prerequisites, no context about typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

4 tool updatesv1.0.0Jan 7, 2026
- First observedget_backlinks_list
- First observedget_traffic
- First observedkeyword_difficulty
- First observedkeyword_generator

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.1/5.0

Scored 2026-04-18 07:15 across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_backlinks_list retrieves backlink data, get_traffic provides traffic estimates, keyword_difficulty assesses keyword competitiveness, and keyword_generator suggests related keywords. There is no overlap in functionality, making tool selection unambiguous.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case: get_backlinks_list, get_traffic, keyword_difficulty, keyword_generator. The naming is predictable and readable, with no deviations in style or convention.

Tool Count4/5

With 4 tools, the count is reasonable for an SEO research server, covering key areas like backlinks, traffic, and keywords. It is slightly lean but not insufficient, as these tools address core SEO analysis needs without being overwhelming.

Completeness3/5

The toolset covers essential SEO research functions but has notable gaps. For example, there are no tools for competitor analysis, content suggestions, or SERP features, which are common in SEO workflows. Agents can perform basic research but may lack comprehensive coverage for advanced tasks.

Maintenance

ActivityStale

ResponsivenessSlow

Resources

GitHub Repository

Need Help?

Reddit Discussion

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