SE Ranking▌
by seranking
AI-friendly MCP server for SE Ranking: run natural-language SEO analysis to find lost or high-op keywords, compare compe
Unlock SEO insights with an AI-friendly MCP server for SE Ranking. This project exposes SE Ranking data as an MCP server so AI assistants can run natural-language SEO analysis. It provides tools to find lost and declining keywords, compare domains against competitors, discover high-volume competitor keywords, and generate related and similar keyword suggestions. Outputs include synthesized reports that highlight low-hanging opportunities using CPC and keyword difficulty metrics. Useful for automated competitive research, keyword discovery, and batch queries. Documentation and support are available at [email protected].
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / SEO professionals doing competitive research
- / Digital marketers optimizing keyword strategies
- / Agencies managing multiple client SEO projects
- / Automated SEO reporting and analysis
capabilities
- / Find lost and declining keywords
- / Compare domains against competitors
- / Discover high-volume competitor keywords
- / Generate related keyword suggestions
- / Analyze backlinks and monitor changes
- / Track website rankings and traffic
what it does
Connects AI assistants to SE Ranking's SEO data for natural language keyword research, competitive analysis, backlink monitoring, and website audits.
about
SE Ranking is an official MCP server published by seranking that provides AI assistants with tools and capabilities via the Model Context Protocol. AI-friendly MCP server for SE Ranking: run natural-language SEO analysis to find lost or high-op keywords, compare compe It is categorized under analytics data.
how to install
You can install SE Ranking in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
SE Ranking is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
SE Ranking MCP Server
This Model Context Protocol (MCP) server connects AI assistants to SE Ranking's SEO data and project management APIs. It enables natural language queries for:
- Keyword research and competitive analysis
- Backlink analysis and monitoring
- Domain traffic and ranking insights
- Website audits and technical SEO
- AI search visibility tracking
- Project and rank tracking management
Prerequisites
Before you begin, please ensure you have the following software and accounts ready:
- SE Ranking Account: You will need an active SE Ranking account to generate an API token. If you don’t have one, you can sign up here.
- Docker: A platform for developing, shipping, and running applications in containers. If you don’t have it, you can download it from the official Docker website.
- Git: A free and open-source distributed version control system. You can download it from the official Git website.
- AI Assistant: You will need an MCP-compatible client, such as Claude Desktop or the Gemini CLI.
API Tokens
This MCP server supports two types of API access:
| Token | Environment Variable | Format | Purpose |
|---|---|---|---|
| Data API | DATA_API_TOKEN | UUID (e.g., 80cfee7d-xxxx-xxxx-xxxx-fc8500816bb3) | Access to keyword research, domain analysis, backlinks data, SERP analysis, and website audits. Tools prefixed with DATA_. |
| Project API | PROJECT_API_TOKEN | 40-char hex (e.g., 253a73adxxxxxxxxxxxx340aa0a939) | Access to project management, rank tracking, backlink monitoring, and account management. Tools prefixed with PROJECT_. |
Get your tokens from: https://online.seranking.com/admin.api.dashboard.html
You can use one or both tokens depending on which tools you need. If you only use Data API tools, you can omit PROJECT_API_TOKEN, and vice versa.
Rate Limits
| API | Default Rate Limit |
|---|---|
| Data API | 10 requests per second |
| Project API | 5 requests per second |
Rate limits are customizable. Contact [email protected] to request adjustments.
Installation
Choose the installation method that best fits your needs:
- Option 1: Docker (Recommended) - Best for standard usage, stability, and ease of updates. Use this if you just want to run the tool without managing dependencies.
- Option 2: Local Node.js Server (For Developers) - Best for development, debugging, or environments where Docker isn't available (like Replit). Use this if you need to modify the code or run a custom setup.
Option 1: Docker (Recommended)
- Open your terminal (or Command Prompt/PowerShell on Windows).
- Clone the project repository from GitHub:
git clone https://github.com/seranking/seo-data-api-mcp-server.git
- Navigate into the new directory:
cd seo-data-api-mcp-server
- Build the Docker Image:
docker build -t se-ranking/seo-data-api-mcp-server .
# Check that the image is built and named `se-ranking/seo-data-api-mcp-server`:
docker image ls
How to Update SEO-MCP (Docker)
To ensure you have the latest features, pull the latest changes and rebuild:
git pull origin main
docker build -t se-ranking/seo-data-api-mcp-server .
Option 2: Local Node.js Server (For Developers)
In order to run the local Node server, you need to have Node.js 20+ version installed on your machine.
- Install dependencies:
npm install
- Build the project:
npm run build
- Start the server:
npm run start-http
Then your HTTP server should be running at: http://0.0.0.0:5000/mcp.
In case you'd like to modify the HOST and PORT, you can do so by creating a .env file in the root directory of the project with the settings you want to override, for example:
HOST=127.0.0.1
PORT=5555
Additionally, when running in external environments like Replit, you can set the DATA_API_TOKEN and PROJECT_API_TOKEN environment variables in the configuration panel.
Note: If you change the API token values when the server is running, you need to restart the server.
Verifying the HTTP Server
To send a sample test request and verify your setup:
./test-http-server-curl-request.sh '<your-api-token-here>'
For batch MCP Requests testing:
./test-batch-http-server-curl-request.sh '<your-api-token-here>'
Connect to Claude Desktop
Claude Desktop reads its configuration from claude_desktop_config.json.
- Click on the Claude menu and select Settings....
- In the Settings window, navigate to the Developer tab in the left sidebar.
- Click the Edit Config button to open the configuration file. This action creates a new configuration file if one doesn’t exist or opens your existing configuration.
The file is located at:
- macOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json - Windows:
%AppData%\Claude\claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Example of Claude Desktop configuration for MCP server
<b>JSON Configuration Template</b>:
{
"mcpServers": {
"seo-data-api-mcp": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DATA_API_TOKEN",
"-e",
"PROJECT_API_TOKEN",
"se-ranking/seo-data-api-mcp-server"
],
"env": {
"DATA_API_TOKEN": "<your-data-api-token-here>",
"PROJECT_API_TOKEN": "<your-project-api-token-here>"
}
}
}
}
-
Replace the
DATA_API_TOKENandPROJECT_API_TOKENplaceholder values with your tokens (see API Tokens section). -
After saving claude_desktop_config.json, restart Claude Desktop. You should see the server under MCP Servers/Tools.
-
To verify the setup, ask Claude:
Do you have access to MCP?It should respond by listingseo-data-api-mcp.

- Your setup is complete! You can now run complex SEO queries using natural language.

Connect to Gemini CLI
- Open the Gemini CLI settings file, which is typically located at:
~/.gemini/settings.json - Add the following JSON configuration, making sure to replace the API token placeholder values.
{
"mcpServers": {
"seo-data-api-mcp": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"DATA_API_TOKEN",
"-e",
"PROJECT_API_TOKEN",
"se-ranking/seo-data-api-mcp-server"
],
"env": {
"DATA_API_TOKEN": "<your-data-api-token-here>",
"PROJECT_API_TOKEN": "<your-project-api-token-here>"
}
}
}
}
Replace the DATA_API_TOKEN and PROJECT_API_TOKEN placeholder values with your tokens (see API Tokens section).
-
Save the configuration file.
-
To verify the setup, launch the Gemini CLI by running
geminiin your terminal. Once the interface is active, pressCtrl+Tto view the available MCP servers. Ensure seo-data-api-mcp is listed.

- Your setup is complete! You can now run complex SEO queries using natural language.

Available Tools
Data API Tools
| Module | Tool Name | Description |
|---|---|---|
| SERP | DATA_getSerpHtmlDump | Retrieves the raw HTML dump of a completed SERP task as a ZIP file. |
| SERP | DATA_getSerpLocations | Retrieves a list of available locations for SERP analysis. |
| SERP | DATA_getSerpResults | Runs a SERP query and returns results. Creates task, polls until complete, and returns organic/ads/featured snippets (standard) or all SERP types including AI Overview, Maps, Reviews (advanced). |
| SERP | DATA_getSerpTaskAdvancedResults | Retrieves the status or advanced results of a specific SERP task. |
| SERP | DATA_getSerpTaskResults | Retrieves the status or standard results of a specific SERP task. Returns organic, ads, and featured_snippet types only. |
| SERP | DATA_getSerpTasks | Retrieves a list of all SERP tasks added to the queue in the last 24 hours. |
| ai search | DATA_getAiDiscoverBrand | Identifies and returns the brand name associated with a given target domain, subdomain, or URL. |
| ai search | DATA_getAiOverview | Retrieves a high-level overview of a domain's performance in AI search engines. |
| ai search | DATA_getAiPromptsByBrand | Retrieves a list of prompts where the specified brand is mentioned in AI search results. |
| ai search | DATA_getAiPromptsByTarget | Retrieves a list of prompts (queries) that mention the specified target in AI search results. |
| backlinks | DATA_exportBacklinksData | Retrieves large-scale backlinks asynchronously, returning a task ID to check status later. |
| backlinks | DATA_getAllBacklinks | Retrieves a comprehensive list of backlinks for the specified target, with extensive filtering and sorting options. |
| backlinks | DATA_getBacklinksAnchors | Retrieves a list of anchor texts for backlinks pointing to the specified target. |
| backlinks | DATA_getBacklinksAuthority | Fetch authority metrics for a target (domain, host or URL). |
| backlinks | DATA_getBacklinksCount | Returns the total number of backlinks for the target. Supports batch requests. |
| backlinks | DATA_getBacklinksExportStatus | Checks the status of an asynchronous backlinks export task. Returns download URL when complete. |
| backlinks | DATA_getBacklinksIndexedPages | Fetch site pages that hav |
FAQ
- What is the SE Ranking MCP server?
- SE Ranking is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for SE Ranking?
- This profile displays 72 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★72 reviews- ★★★★★Arya Jackson· Dec 28, 2024
We evaluated SE Ranking against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Ren Park· Dec 24, 2024
SE Ranking has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Arya Huang· Dec 20, 2024
Useful MCP listing: SE Ranking is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Maya Robinson· Dec 16, 2024
SE Ranking is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Pratham Ware· Dec 12, 2024
According to our notes, SE Ranking benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Hiroshi Khanna· Dec 12, 2024
Strong directory entry: SE Ranking surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ama Haddad· Dec 4, 2024
We evaluated SE Ranking against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Maya Chawla· Nov 27, 2024
According to our notes, SE Ranking benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Dev Choi· Nov 15, 2024
We evaluated SE Ranking against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kwame Martinez· Nov 15, 2024
SE Ranking is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
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