Firecrawl MCP vs Jina Reader MCP: Which Web Scraping Server Should You Use?

Your AI coding assistant needs to read web pages. Maybe it is pulling documentation, checking a competitor's pricing page, or scraping product data for a side project. Two MCP servers dominate this space: Firecrawl MCP and Jina Reader MCP.

They solve the same core problem -- get clean, usable content from a URL -- but they take very different approaches. Firecrawl is a full crawling engine with structured extraction. Jina Reader is a lightweight API that converts URLs to clean markdown. This guide compares them side by side so you pick the right one for your workflow.

The Comparison Table

The numbers that matter most here are tool count and estimated tokens. Firecrawl registers roughly 10 tools with your AI assistant, consuming about 8,000 tokens from your context window before you even start working. Jina Reader registers about 3 tools at roughly 3,000 tokens -- less than half the overhead.

When to Choose Firecrawl MCP

Firecrawl is the heavier tool. You pay for that weight with tokens, but you get capabilities that Jina Reader simply does not offer.

Crawling entire sites. If you need to ingest all the pages from a documentation site, a sitemap, or a product catalog, Firecrawl's crawl tool handles this natively. You point it at a root URL and it follows links, respects robots.txt, and returns structured results. Jina Reader works one page at a time.

Structured data extraction. Firecrawl can extract specific fields from pages using LLM-powered extraction. Need just the price, product name, and availability from 50 product pages? Firecrawl's extract tool lets you define a schema and pulls exactly those fields. Jina Reader returns the full markdown and leaves the parsing to you (or your AI assistant's context window).

Self-hosting for privacy or cost control. Firecrawl is open source. You can run your own instance and avoid sending URLs through a third-party API. For teams with compliance requirements or high-volume scraping needs, this matters. Jina Reader is API-only.

Research pipelines. If you are building a workflow that processes many pages -- competitive analysis, market research, content aggregation -- Firecrawl's combination of crawl, map, and extract tools gives you a pipeline inside your AI assistant. The 8,000-token overhead is worth it when you are making heavy use of all those tools.

Token budget is less of a concern. If Firecrawl is the only MCP server you are running, or you have plenty of context window to spare, the extra tokens are not a problem.

When to Choose Jina Reader MCP

Jina Reader is the lighter tool. It does fewer things, but it does them with less overhead and less complexity.

Reading individual pages. The most common web scraping use case in AI-assisted coding is simple: "read this URL and tell me what it says." Jina Reader is built exactly for this. You give it a URL, it returns clean markdown. Done.

Token budget matters. At roughly 3,000 tokens, Jina Reader is one of the lightest MCP servers you can run. If you are already loading GitHub MCP, a database server, and a file system server, those tokens add up fast. Jina Reader keeps your web reading capability without blowing your context budget.

Simplest possible setup. Three tools. One API key. No decisions about crawl depth, extraction schemas, or output formats. If you want to add web reading to your AI assistant with minimal configuration, Jina Reader is the path of least resistance.

Search and read workflows. Jina Reader includes a search tool that finds relevant pages and a read tool that fetches them. For the common pattern of "find information about X and summarize it," this covers the full loop.

Built-in fact-checking. Jina Reader includes a fact-check tool that can verify claims against web sources. This is a niche feature but useful if you are using your AI assistant to research topics where accuracy matters.

Setup: Firecrawl MCP

Firecrawl requires an API key from firecrawl.dev. The free tier gives you 500 credits per month, which is enough for light usage.

For Claude Desktop, Cursor, or any MCP-compatible client:

{
  "mcpServers": {
    "firecrawl": {
      "command": "npx",
      "args": ["-y", "firecrawl-mcp"],
      "env": {
        "FIRECRAWL_API_KEY": "<your-key>"
      }
    }
  }
}

If you are self-hosting Firecrawl, you can point the MCP server at your own instance by setting the FIRECRAWL_API_URL environment variable alongside your key.

Setup: Jina Reader MCP

Jina Reader requires an API key from jina.ai. The free tier is generous for individual developers.

{
  "mcpServers": {
    "jina-reader": {
      "command": "npx",
      "args": ["-y", "jina-reader-mcp"],
      "env": {
        "JINA_API_KEY": "<your-key>"
      }
    }
  }
}

That is the entire setup. No additional configuration needed.

Can You Use Both?

Technically, yes. You can run both Firecrawl MCP and Jina Reader MCP in the same client configuration. But there are good reasons not to.

Running both servers adds roughly 11,000 tokens to your context window just for tool definitions. You also end up with overlapping capabilities -- both can scrape a single page, both can search the web. Your AI assistant has to decide which server to use for each request, which can lead to inconsistent behavior.

A better approach: pick one based on your primary use case. If you mostly read individual pages and want low overhead, go with Jina Reader. If you need crawling, extraction, or self-hosting, go with Firecrawl. If you occasionally need the other server's features, you can always swap your config. It takes 30 seconds.

What About Exa MCP?

Exa is a third option worth mentioning, but it solves a different problem. Where Firecrawl and Jina Reader focus on reading known URLs, Exa focuses on semantic search -- finding the most relevant pages for a query using neural search rather than keyword matching.

If your primary need is "find the best pages about X," Exa is strong. If your primary need is "read this specific URL," Firecrawl or Jina Reader is the better choice. They are complementary tools, not direct competitors.

You can explore Exa and other web-related MCP servers at stackmcp.dev/servers.

The Verdict

For most developers, Jina Reader MCP is the better default choice. It covers roughly 80% of web scraping use cases -- reading pages, searching, and summarizing content -- at less than half the token cost of Firecrawl. The setup is trivial, the free tier is generous, and three tools are easier for your AI assistant to reason about than ten.

Choose Firecrawl MCP if you need power features. Batch crawling, structured data extraction, and self-hosting are real capabilities that Jina Reader does not offer. If you are building data pipelines, scraping product catalogs, or ingesting entire documentation sites through your AI assistant, Firecrawl is the right tool.

The deciding question is simple: do you need to read pages, or do you need to crawl sites? Read pages, pick Jina. Crawl sites, pick Firecrawl.

Get either one configured in under a minute at stackmcp.dev. Select your web scraping server, pick your AI client, and copy the generated JSON.