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DataForSEO

Organization
dataforseo

DataForSEO API modelcontextprotocol server

Publisherdataforseo
Repositorymcp-server-typescript
LanguageTypeScript
Forks
111
Stars
196
Available tools
0
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    DataForSEO exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    196 stars and 111 forks from the linked repository.

DataForSEO MCP Server

Model Context Protocol (MCP) server implementation for DataForSEO, enabling AI assistants to interact with selected DataForSEO APIs and obtain SEO data through a standardized interface.

Features

  • AI_OPTIMIZATION API: provides data for keyword discovery, conversational optimization, and real-time LLM benchmarking;
  • SERP API: real-time Search Engine Results Page (SERP) data for Google, Bing, and Yahoo;
  • KEYWORDS_DATA API: keyword research and clickstream data, including search volume, cost-per-click, and other metrics;
  • ONPAGE API: allows crawling websites and webpages according to customizable parameters to obtain on-page SEO performance metrics;
  • DATAFORSEO LABS API: data on keywords, SERPs, and domains based on DataForSEO's in-house databases and proprietary algorithms;
  • BACKLINKS API: comprehensive backlink analysis including referring domains, anchor text distribution, and link quality metrics;
  • BUSINESS DATA API: publicly available data on any business entity;
  • DOMAIN ANALYTICS API: data on website traffic, technologies, and Whois details;
  • CONTENT ANALYSIS API: robust source of data for brand monitoring, sentiment analysis, and citation management;

Prerequisites

  • Node.js (v14 or higher)
  • DataForSEO API credentials (API login and password)

Installation

  1. Clone the repository:
bash
git clone https://github.com/dataforseo/mcp-server-typescript
cd mcp-server-typescript
  1. Install dependencies:
bash
npm install
  1. Set up environment variables:
bash
# Required
export DATAFORSEO_USERNAME=your_username
export DATAFORSEO_PASSWORD=your_password

# Optional: specify which modules to enable (comma-separated)
# If not set, all modules will be enabled
export ENABLED_MODULES="SERP,KEYWORDS_DATA,ONPAGE,DATAFORSEO_LABS,BACKLINKS,BUSINESS_DATA,DOMAIN_ANALYTICS"

# Optional: specify which prompts in enabled modules are enable too (prompts names, comma-separated)
# If not set, all prompts from enabled modules will be enabled
export ENABLED_PROMPTS="top_3_google_result_domains,top_5_serp_paid_and_organic"

# Optional: enable full API responses
# If not set or set to false, the server will filter and transform API responses to a more concise format
# If set to true, the server will return the full, unmodified API responses
export DATAFORSEO_FULL_RESPONSE="false"

# Optional: enable simple filter schema
# If set to true, a simplified version of the filters schema will be used.
# This is required for ChatGPT APIs or other LLMs that cannot handle nested structures.
export DATAFORSEO_SIMPLE_FILTER="false"

Installation as an NPM Package

You can install the package globally:

bash
npm install -g dataforseo-mcp-server

Or run it directly without installation:

bash
npx dataforseo-mcp-server

Remember to set environment variables before running the command:

bash
# Required environment variables
export DATAFORSEO_USERNAME=your_username
export DATAFORSEO_PASSWORD=your_password

# Run with npx
npx dataforseo-mcp-server

Building and Running

Build the project:

bash
npm run build

Run the server:

bash
# Start local server (direct MCP communication)
npx dataforseo-mcp-server

# Start HTTP server
npx dataforseo-mcp-server http

HTTP Server Configuration

The server runs on port 3000 by default and supports both Basic Authentication and environment variable-based authentication.

To start the HTTP server, run:

bash
npm run http

Authentication Methods

  1. Basic Authentication

    • Send requests with Basic Auth header:
    Authorization: Basic <base64-encoded-credentials>
    • Credentials format: username:password
  2. Environment Variables

    • If no Basic Auth is provided, the server will use credentials from environment variables:
    bash
    export DATAFORSEO_USERNAME=your_username
    export DATAFORSEO_PASSWORD=your_password
    # Optional
    export DATAFORSEO_SIMPLE_FILTER="false"
    export DATAFORSEO_FULL_RESPONSE="true"

Cloudflare Worker Deployment

The DataForSEO MCP Server can be deployed as a Cloudflare Worker for serverless, edge-distributed access to DataForSEO APIs.

Worker Features

  • Edge Distribution: Deploy globally across Cloudflare's edge network
  • Serverless: No server management required
  • Auto-scaling: Handles traffic spikes automatically
  • MCP Protocol Support: Compatible with both Streamable HTTP and SSE transports
  • Environment Variables: Secure credential management through Cloudflare dashboard

Quick Start

  1. Install Wrangler CLI:

    bash
    npm install -g wrangler
  2. Configure Worker:

    bash
    # Login to Cloudflare
    wrangler login
    
    # Set environment variables
    wrangler secret put DATAFORSEO_USERNAME
    wrangler secret put DATAFORSEO_PASSWORD
  3. Deploy Worker:

    bash
    # Build and deploy
    npm run build
    wrangler deploy --main build/index-worker.js

Configuration

The worker uses the same environment variables as the standard server:

  • DATAFORSEO_USERNAME: Your DataForSEO username
  • DATAFORSEO_PASSWORD: Your DataForSEO password
  • ENABLED_MODULES: Comma-separated list of modules to enable
  • ENABLED_PROMPTS: Comma-separated list of prompt names to enable
  • DATAFORSEO_FULL_RESPONSE: Set to "true" for full API responses

Worker Endpoints

Once deployed, your worker will be available at https://your-worker.your-subdomain.workers.dev/ with the following endpoints:

  • POST /mcp: Streamable HTTP transport (recommended)
  • GET /sse: SSE connection establishment (deprecated)
  • POST /messages: SSE message handling (deprecated)
  • GET /health: Health check endpoint
  • GET /: API documentation page

Advanced Configuration

Edit wrangler.jsonc to customize your deployment:

jsonc
{
  "name": "dataforseo-mcp-worker",
  "main": "build/index-worker.js",
  "compatibility_date": "2025-07-10",
  "compatibility_flags": ["nodejs_compat"],
  "vars": {
    "ENABLED_MODULES": "SERP,KEYWORDS_DATA,ONPAGE,DATAFORSEO_LABS",
    "ENABLED_PROMPTS":"top_3_google_result_domains,top_5_serp_paid_and_organic"
  }
}

Usage with Claude

After deployment, configure Claude to use your worker:

json
{
  "name": "DataForSEO",
  "description": "Access DataForSEO APIs via Cloudflare Worker",
  "transport": {
    "type": "http",
    "baseUrl": "https://your-worker.your-subdomain.workers.dev/mcp"
  }
}

Available Modules

The following modules are available to be enabled/disabled:

  • AI_OPTIMIZATION: provides data for keyword discovery, conversational optimization, and real-time LLM benchmarking;
  • SERP: real-time SERP data for Google, Bing, and Yahoo;
  • KEYWORDS_DATA: keyword research and clickstream data;
  • ONPAGE: crawl websites and webpages to obtain on-page SEO performance metrics;
  • DATAFORSEO_LABS: data on keywords, SERPs, and domains based on DataForSEO's databases and algorithms;
  • BACKLINKS: data on inbound links, referring domains and referring pages for any domain, subdomain, or webpage;
  • BUSINESS_DATA: based on business reviews and business information publicly shared on the following platforms: Google, Trustpilot, Tripadvisor;
  • DOMAIN_ANALYTICS: helps identify all possible technologies used for building websites and offers Whois data;
  • CONTENT_ANALYSIS: help you discover citations of the target keyword or brand and analyze the sentiments around it;

Adding New Tools/Modules

Module Structure

Each module corresponds to a specific DataForSEO API:

Implementation Options

You can either:

  1. Add a new tool to an existing module
  2. Create a completely new module

Adding a New Tool

Here's how to add a new tool to any new or pre-existing module:

typescript
// src/code/modules/your-module/tools/your-tool.tool.ts
import { BaseTool } from '../../base.tool';
import { DataForSEOClient } from '../../../client/dataforseo.client';
import { z } from 'zod';

export class YourTool extends BaseTool {
  constructor(private client: DataForSEOClient) {
    super(client);
    // DataForSEO API returns extensive data with many fields, which can be overwhelming
    // for AI agents to process. We select only the most relevant fields to ensure
    // efficient and focused responses.
    this.fields = [
      'title',           // Example: Include the title field
      'description',     // Example: Include the description field
      'url',            // Example: Include the URL field
      // Add more fields as needed
    ];
  }

  getName() {
    return 'your-tool-name';
  }

  getDescription() {
    return 'Description of what your tool does';
  }

  getParams(): z.ZodRawShape {
    return {
      // Required parameters
      keyword: z.string().describe('The keyword to search for'),
      location: z.string().describe('Location in format "City,Region,Country" or just "Country"'),
      
      // Optional parameters
      fields: z.array(z.string()).optional().describe('Specific fields to return in the response. If not specified, all fields will be returned'),
      language: z.string().optional().describe('Language code (e.g., "en")'),
    };
  }

  async handle(params: any) {
    try {
      // Make the API call
      const response = await this.client.makeRequest({
        endpoint: '/v3/dataforseo_endpoint_path',
        method: 'POST',
        body: [{
          // Your request parameters
          keyword: params.keyword,
          location: params.location,
          language: params.language,
        }],
      });

      // Validate the response for errors
      this.validateResponse(response);

      //if the main data array is specified in tasks[0].result[:] field
      const result = this.handleDirectResult(response);
      //if main data array specified in tasks[0].result[0].items field
      const result = this.handleItemsResult(response);
      // Format and return the response
      return this.formatResponse(result);
    } catch (error) {
      // Handle and format any errors
      return this.formatErrorResponse(error);
    }
  }
}

Creating a New Module

  1. Create a new directory under src/core/modules/ for your module:
bash
mkdir -p src/core/modules/your-module-name
  1. Create module files:
typescript
// src/core/modules/your-module-name/your-module-name.module.ts
import { BaseModule } from '../base.module';
import { DataForSEOClient } from '../../client/dataforseo.client';
import { YourTool } from './tools/your-tool.tool';

export class YourModuleNameModule extends BaseModule {
  constructor(private client: DataForSEOClient) {
    super();
  }

  getTools() {
    return {
      'your-tool-name': new YourTool(this.client),
    };
  }
}
  1. Register your module in src/core/config/modules.config.ts:
typescript
export const AVAILABLE_MODULES = [
  'SERP',
  'KEYWORDS_DATA',
  'ONPAGE',
  'DATAFORSEO_LABS',
  'BACKLINKS',
  'BUSINESS_DATA',
  'DOMAIN_ANALYTICS',
  'CONTENT_ANALYSIS',
  'YOUR_MODULE_NAME'  // Add your module name here
] as const;
  1. Initialize your module in src/main/index.ts:
typescript
if (isModuleEnabled('YOUR_MODULE_NAME', enabledModules)) {
  modules.push(new YourModuleNameModule(dataForSEOClient));
}

Field Configuration

The MCP server supports field filtering to customize which data fields are returned in API responses. This helps reduce response size and focus on the most relevant data for your use case.

Configuration File Format

Create a JSON configuration file with the following structure:

json
{
  "supported_fields": {
    "tool_name": ["field1", "field2", "field3"],
    "another_tool": ["field1", "field2"]
  }
}

Using Field Configuration

Pass the configuration file using the --configuration parameter:

bash
# With npm
npm run cli -- http --configuration field-config.json

# With npx
npx dataforseo-mcp-server http --configuration field-config.json

# Local mode
npx dataforseo-mcp-server local --configuration field-config.json

Configuration Behavior

  • If a tool is configured: Only the specified fields will be returned in the response
  • If a tool is not configured: All available fields will be returned (default behavior)
  • If no configuration file is provided: All tools return all available fields

Example Configuration File

The repository includes an example configuration file field-config.example.json with optimized field selections for common tools:

json
{
  "supported_fields": {
    "backlinks_backlinks": [
      "id",
      "items.anchor",
      "items.backlink_spam_score",
      "items.dofollow",
      "items.domain_from",
      "items.domain_from_country",
      "items.domain_from_ip",
      "items.domain_from_platform_type",
      "items.domain_from_rank",
      "items.domain_to",
      "items.first_seen",
      "items.is_broken",
      "items.is_new",
      "items.item_type",
      "items.last_seen",
      "items.links_count",
      "items.original",
      "items.page_from_encoding",
      "items.page_from_external_links",
      "items.page_from_internal_links",
      "items.page_from_language",
      "items.page_from_rank",
      "items.page_from_size",
      "items.page_from_status_code",
      "items.page_from_title",
      "items.prev_seen",
      "items.rank",
      "items.ranked_keywords_info.page_from_keywords_count_top_10",
      "items.ranked_keywords_info.page_from_keywords_count_top_100",
      "items.ranked_keywords_info.page_from_keywords_count_top_3",
      "items.semantic_location",
      "items.text_post",
      "items.text_pre",
      "items.tld_from",
      "items.type",
      "items.url_from",
      "items.url_from_https",
      "items.url_to",
      "items.url_to_https",
      "items.url_to_spam_score",
      "items.url_to_status_code",
      "status_code",
      "status_message"
    ],
    ...
  }
}

Nested Field Support

The configuration supports nested field paths using dot notation:

  • "rating.value" - Access the value field within the rating object
  • "items.demography.age.keyword" - Access deeply nested fields
  • "meta.description" - Access nested object properties

Field Discovery

To discover available fields for any tool:

  1. Run the tool without field configuration to see the full response
  2. Identify the fields you need from the API response
  3. Add those field paths to your configuration file

Creating Your Own Configuration

  1. Copy the example file:
bash
cp field-config.example.json my-config.json
  1. Modify the field selections based on your needs

  2. Use your custom configuration:

bash
npx dataforseo-mcp-server http --configuration my-config.json

What endpoints/APIs do you want us to support next?

We're always looking to expand the capabilities of this MCP server. If you have specific DataForSEO endpoints or APIs you'd like to see supported, please:

  1. Check the DataForSEO API Documentation to see what's available
  2. Open an issue in our GitHub repository with:
    • The API/endpoint you'd like to see supported;
    • A brief description of your use case;
    • Describe any specific features you'd like to see implemented.

Your feedback helps us prioritize which APIs to support next!

Resources

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "data-for-seo": {
      "command": "npx",
      "args": [
        "dataforseo-mcp-server"
      ],
      "env": {
        "DATAFORSEO_USERNAME": "your_username",
        "DATAFORSEO_PASSWORD": "your_password"
      }
    }
  }
}

Use DataForSEO MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once DataForSEO is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add DataForSEO as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the DataForSEO MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "dataforseo": {
      "command": "npx",
      "args": [
        "-y",
        "dataforseo-mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the DataForSEO MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the DataForSEO MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use DataForSEO to help me with this task?
DataForSEO
Sure. I read it.
Here is what I found using DataForSEO.

Frequently asked questions

What is the DataForSEO MCP server used for?

DataForSEO is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use DataForSEO MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use DataForSEO with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use DataForSEO MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With DataForSEO connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect DataForSEO MCP to TypingMind?

DataForSEO runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does DataForSEO MCP provide in TypingMind?

DataForSEO exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use DataForSEO MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If DataForSEO requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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