Olostep MCP Server
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License: ISC
Live web search, scraping and crawling API for AI. Get structured, LLM-ready data from any site. Scale to 1M requests with 10 parallel batches at low cost.
Olostep is web data infrastructure for AI agents and enterprise AI workflows. Its APIs provide live web search, scraping and crawling to extract, clean and structure data from the web. This is the official Olostep Model Context Protocol (MCP) server, which gives any MCP-compatible AI agent those capabilities.
Use the hosted server at https://mcp.olostep.com/mcp (sign in with OAuth, or use an API key), or run it locally with an API key from the Olostep website.
Why Olostep
- Web data infrastructure for developers and enterprises
- Scales to hundreds of millions to billions of requests per customer per month
- The most performant, reliable and cost-effective API on the market
- Used by the fastest-growing AI companies
From extracting data from a handful of URLs to crawling hundreds of millions of pages, Olostep gives developers and AI companies reliable, scalable and highly cost-effective access to clean, structured web data.
Features
- Scrape website content in HTML, Markdown, JSON or Plain Text (with optional parsers)
- Parser-based web search with structured results
- AI Answers with citations and optional JSON-shaped outputs
- Batch scraping of up to 100k URLs
- Autonomous site crawling from a start URL
- Website URL discovery and mapping (with include/exclude filters)
- Country-specific request routing for geo-targeted content
- Configurable wait times for JavaScript-heavy websites
- Comprehensive error handling and reporting
- Simple API key configuration
Installation
There are multiple ways to connect to the Olostep MCP Server. Choose the one that best fits your workflow.
One-click install
Connect to the hosted server and sign in with your Olostep account (OAuth). No API key or local setup needed.
[Install in Cursor]
[Install in VS Code]
[Add to Replit]
[Add to Claude]
[Add to ChatGPT]
Or from the terminal:
For other clients, see Client Setup.
☁️ Remote Endpoint (Recommended)
The simplest way — no local installation required. Connect directly to our hosted MCP server:
Authentication is done via a Bearer token in the Authorization header using your Olostep API key. See the Client Setup section below for configuration examples.
🐳 Docker Hub
Pull and run the official Docker image:
🔧 Local Docker Build
If you prefer to build the image yourself from source:
📦 npx
Run without any installation using npx:
On Windows (PowerShell):
On Windows (CMD):
Or install globally:
Client Setup
Gemini CLI
Install the Olostep extension in Gemini CLI (requires an Olostep API key):
Configure your API key through Gemini CLI's sensitive extension settings:
Gemini CLI stores this value in your system keychain. Restart Gemini CLI, then verify the extension and MCP server:
For authentication errors, configure the key again. For connection errors, restart Gemini CLI and run gemini mcp list. See the official Gemini CLI extensions documentation for details.
Cursor
The easiest way is to use the remote endpoint. Create or edit .cursor/mcp.json in your project root:
Alternative (local): Go to Cursor Settings > Features > MCP Servers, click "+ Add New MCP Server":
- Name:
olostep
- Type:
command
- Command:
env OLOSTEP_API_KEY=your-api-key npx -y olostep-mcp
Claude Desktop
Add this to your claude_desktop_config.json:
Alternative (Docker):
Or install via the Smithery CLI in your device terminal:
Claude Code
Add the remote endpoint to your Claude Code MCP configuration:
Alternative (local):
Windsurf
Add this to your ./codeium/windsurf/model_config.json:
Alternative (local):
Cline
Add this to your cline_mcp_settings.json (Cline → MCP Servers → Configure):
Cline can also set this up for you: ask it to install the MCP server from this repository, and it follows llms-install.md.
VS Code
Add this to your .vscode/mcp.json:
Alternative (local):
GitHub Copilot CLI
Inside Copilot CLI, run /mcp add and enter:
- Name:
olostep
- Type: HTTP
- URL:
https://mcp.olostep.com/mcp
- Headers: leave empty
Save with Ctrl+S, then sign in with your Olostep account when prompted (OAuth). Check the connection with /mcp show olostep.
This writes the following to ~/.copilot/mcp-config.json:
Zed
Add this to your Zed settings.json:
Alternative (extension): the Olostep Zed extension runs the local server and asks for your API key in Zed's setup screen.
Metorial
Option 1: One-Click Installation (Recommended)
- Open Metorial dashboard
- Navigate to MCP Servers directory
- Search for "Olostep"
- Click "Install" and enter your API key
Option 2: Manual Configuration
Add this to your Metorial MCP server configuration:
The Olostep tools will then be available in your Metorial AI chats.
Configuration
Environment Variables
OLOSTEP_API_KEY: Your Olostep API key (required)
ORBIT_KEY: An optional key for using Orbit to route requests.
Available Tools
1. Scrape Website (scrape_website)
Extract content from a single URL. Supports multiple formats and JavaScript rendering.
Parameters:
url_to_scrape: The URL of the website you want to scrape (required)
output_format: Choose format (html, markdown, json, or text) - default: markdown
country: Optional country code (e.g., US, GB, CA) for location-specific scraping
wait_before_scraping: Wait time in milliseconds before scraping (0-10000)
parser: Optional parser ID for specialized extraction
Response (example):
2. Search the Web (search_web)
Search the Web for a given query and get structured results (non-AI, parser-based).
Parameters:
query: Search query (required)
country: Optional country code for localized results (default: US)
Response:
- Structured JSON (as text) representing parser-based results
3. Answers (AI) (answers)
Search the web and return AI-powered answers in the JSON structure you want, with sources and citations.
Parameters:
task: Question or task to answer using web data (required)
json: Optional JSON schema/object or a short description of the desired output shape
Response includes:
answer_id, object, task, result (JSON if provided), sources, created
4. Batch Scrape URLs (batch_scrape_urls)
Scrape up to 100k URLs in one batch. Perfect for large-scale data extraction. New accounts start at 100 URLs per batch, and [email protected] can lift this.
Response includes:
batch_id, status, total_urls, created_at, formats, country, parser, urls
5. Create Crawl (create_crawl)
Start an async crawl that autonomously discovers and scrapes entire websites by following links. Returns a crawl_id — the crawl runs in the background and does not return content in this response. You must then call get_crawl_results with the crawl_id to poll status and retrieve the scraped pages (same two-step pattern as batch_scrape_urls + get_batch_results).
Response includes:
crawl_id, object, status, start_url, max_pages, created, formats, country, parser
Pair this call with get_crawl_results — do not pass a crawl_id to get_batch_results (crawls and batches are separate resources).
6. Create Map (create_map)
Get all URLs on a website. Extract all URLs for discovery and analysis.
Response includes:
map_id, object, url, total_urls, urls, search_query, top_n
7. Get Webpage Content (get_webpage_content)
Retrieves webpage content in clean markdown format with support for JavaScript rendering.
Parameters:
url_to_scrape: The URL of the webpage to scrape (required)
wait_before_scraping: Time to wait in milliseconds before starting the scrape (default: 0)
country: Residential country to load the request from (e.g., US, CA, GB) (optional)
Response:
8. Get Website URLs (get_website_urls)
Search and retrieve relevant URLs from a website, sorted by relevance to your query.
Parameters:
url: The URL of the website to map (required)
search_query: The search query to sort URLs by (required)
Response:
9. Get Batch Results (get_batch_results)
Retrieve the results of a previously submitted batch scrape job using its batch_id.
Parameters:
batch_id: The batch ID returned from batch_scrape_urls (required)
items_limit: Max items to retrieve content for per call, 1–100 (default: 20)
cursor: Pass next_cursor from the previous result to get the next pages (default: 0)
Large batches return their pages a set at a time. When has_more is true, call again with next_cursor until you have every page.
Response includes:
batch_id, status (processing or completed), total_urls, completed_urls, items (array of scraped results per URL with url, custom_id, markdown_content, html_content, json_content, text_content, status, page_metadata)
10. Get Crawl Results (get_crawl_results)
Retrieve the status and scraped pages for an async crawl started with create_crawl. This is the required companion to create_crawl — create_crawl only kicks off the job and returns a crawl_id; this tool is how you actually fetch the discovered pages and their content.
Parameters:
crawl_id: The crawl ID returned from create_crawl (required)
formats: Array of formats to retrieve per page — markdown, html, json, text (default: ["markdown"])
items_limit: Max pages to retrieve content for, 1–100 (default: 20)
cursor: Pagination cursor into the list of discovered pages (default: 0)
search_query: Optional filter to rank/select pages by relevance to a query
Response includes:
- While in progress:
crawl_id, status (in_progress), pages_completed, pages_total, and a message prompting you to call again in ~10 seconds.
- When completed:
crawl_id, status (completed), pages_returned, next_cursor, has_more, and a pages array where each entry has url, custom_id, and the requested content fields (markdown_content, html_content, json_content, text_content).
Error Handling
The server provides robust error handling:
- Detailed error messages for API issues
- Network error reporting
- Authentication failure handling
- Rate limit information
Example error response:
Distribution
Docker Images
The MCP server is available as a Docker image:
- Docker Hub:
[olostep/mcp-server](https://hub.docker.com/r/olostep/mcp-server)
- Official Docker MCP Registry:
mcp/olostep (coming soon - enhanced security with signatures & SBOMs)
- GitHub Container Registry:
ghcr.io/olostep/olostep-mcp-server
Docker Desktop MCP Toolkit
The Olostep MCP Server is being added to Docker Desktop's official MCP Toolkit, which means users will be able to:
- Discover it in Docker Desktop's MCP Toolkit UI
- Install it with one click
- Configure it visually
- Use it with any MCP-compatible client (Claude Desktop, Cursor, etc.)
Status: Submission in progress to Docker MCP Registry
Supported Platforms
Building Locally
About Olostep
Olostep is web data infrastructure for AI. It provides live web search, scraping and crawling API to extract and structure data, used in production by AI companies to give their agents fresh, LLM-ready web data at scale.
License
ISC License