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The Apify MCP server enables your AI agents to extract data from social media, search engines, maps, e-commerce sites, or any other website using thousands of ready-made scrapers, crawlers, and automation tools available on the Apify Store.
This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.
100
review score
Problem solved
It solves the problem of giving AI agents real-time, structured web data access without building custom scrapers or dealing with anti-bot measures. It abstracts away the complexity of web scraping, providing a standardized MCP interface to a vast ecosystem of pre-built, maintained scrapers, which would otherwise require significant engineering effort.
Deployment reality
The available setup signal starts with: npx @apify/actors-mcp-server. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build AI agents that perform tasks like monitoring social media, extracting business leads from maps, aggregating search results, or gathering e-commerce product data. The ceiling is high: with access to thousands of Actors, agents can automate virtually any web data extraction task, including complex multi-step workflows, and can even handle payments for premium Actors. Real-world use cases include competitive intelligence, lead generation, market research, and content aggregation.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
apify/apify-mcp-server is tracked as a TypeScript project in the AI Agent, MCP Server, Automation, Data Tool, Infrastructure area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 3.6k total stars, with +136 today, +0 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Active; the latest push was 10 days ago, and the open issue queue is 127, about 3.58% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 222 forks and 3.6k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need AI prototypes, LLM workflows, and agent-style applications. Be cautious when you have low tolerance for large unresolved issue queues.
Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 136. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
ReadyRepository metadata and README/source references are attached.
License
ReadyMIT is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
3.6k Stars
Reuse
222 Forks
Attention
3.6k Watchers
Maintenance
active
License
MIT
Open issues
127
The Apify Model Context Protocol (MCP) server enables AI agents to extract data from social media, search engines, maps, e-commerce sites, and any other website using thousands of ready-made scrapers, crawlers, and automation tools from the Apify Store. It supports OAuth for easy connection from clients like Claude.ai or Visual Studio Code, and offers both a hosted HTTPS endpoint and a local stdio option.
Key Features
- Access to thousands of ready-made scrapers and automation tools from Apify Store - Supports OAuth for easy connection from popular MCP clients like Claude.ai and VS Code - Offers both hosted HTTPS endpoint and local stdio deployment options
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
MCP Server
Model Context Protocol servers, clients, and integrations
Automation
Workflow automation, integration glue, and orchestration
Data Tool
Databases, data pipelines, ETL, analytics, and vector search
Infrastructure
Cloud, deployment, networking, containers, and platform tooling
npx @apify/actors-mcp-server73
Health Score
Active
Commit Activity
Jan 2, 2025
Created
Aug 13, 2026
Last push
+0
Today's growth
+0
7-day growth
+0
30-day growth
Forks
Open
Watchers
apify
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✓
License
✓
Forked
✓ Active
Maintained
Problem Solved
It solves the problem of giving AI agents real-time, structured web data access without building custom scrapers or dealing with anti-bot measures. It abstracts away the complexity of web scraping, providing a standardized MCP interface to a vast ecosystem of pre-built, maintained scrapers, which would otherwise require significant engineering effort.
Capabilities
Developers can build AI agents that perform tasks like monitoring social media, extracting business leads from maps, aggregating search results, or gathering e-commerce product data. The ceiling is high: with access to thousands of Actors, agents can automate virtually any web data extraction task, including complex multi-step workflows, and can even handle payments for premium Actors. Real-world use cases include competitive intelligence, lead generation, market research, and content aggregation.
Bottom Line
This framework is ideal for developers and organizations that need to integrate web data extraction into AI agents quickly and at scale, without building scraping infrastructure. It should be avoided by those who require fully custom, niche scraping solutions or who have strict data compliance concerns that a third-party service cannot address. The key trade-off is convenience and breadth of tools versus reliance on a commercial platform and potential ethical/legal risks of automated web scraping.