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screamingfrog-audit-mcp

CI PyPI Python 3.10+ License: MIT

Drive the Screaming Frog SEO Spider from Claude, Cursor, or any other MCP client. Crawl a site, get a ranked issue register back, ask questions of the crawl data, and render a shareable report — without opening the GUI or writing a single command.

It works on the free, unlicensed SEO Spider

That is the point of this server, and it is unusual: the other MCP servers for Screaming Frog build on its saved-crawl database, which is a licensed feature, so they need a paid install. This one drives the crawl directly and never touches that database.

The free tier caps you at 500 URLs per invocation — not per site. So full=true reads robots.txt and the sitemaps, splits the URLs into batches under the cap, runs each through list mode, and merges the exports. A 3,000-page site audits completely on a free install.

A licence removes the cap and unlocks config= for JavaScript rendering and custom extraction. Both tiers are supported and the server adapts to whichever you have.

You:  Crawl example.com and tell me what's actually broken.

→ start_crawl(url="https://example.com")
→ crawl_status()                     # 248 URLs, 51s
→ get_issues(priority="High")

Claude: Three high-priority problems. The big one: robots.txt disallows
/_next/, which hides 85 JS and CSS bundles from Google...

Install

Two prerequisites: Python 3.10+ and the Screaming Frog SEO Spider installed on the same machine (download). The free version is fine — see the free-tier situation.

Every setup below uses uvx, which downloads and runs the package on demand with no virtualenv to manage. It ships with uv: curl -LsSf https://astral.sh/uv/install.sh | sh (macOS/Linux) or powershell -c "irm https://astral.sh/uv/install.ps1 | iex" (Windows).

Prefer pip? pip install screamingfrog-audit-mcp, then use "command": "screamingfrog-audit-mcp" with "args": [] in any config below.

Claude Code

claude mcp add screaming-frog -- uvx screamingfrog-audit-mcp

Add -s user to make it available in every project rather than just this one.

Claude Desktop

Settings → Developer → Edit Config, which opens claude_desktop_config.json:

OS Path
macOS ~/Library/Application Support/Claude/claude_desktop_config.json
Windows %APPDATA%\Claude\claude_desktop_config.json

Use the full path to uvx, not just uvx. Claude Desktop is a GUI app and does not inherit your shell PATH, so a bare command is not found and the app reports a dead server with no reason given. This is the single most common reason an MCP server "does not work" in Claude Desktop.

Get the path with which uvx (macOS/Linux) or where uvx (Windows) — usually /Users/you/.local/bin/uvx or C:\Users\you\.local\bin\uvx.exe:

{
  "mcpServers": {
    "screaming-frog": {
      "command": "/Users/you/.local/bin/uvx",
      "args": ["screamingfrog-audit-mcp"]
    }
  }
}

If the file already has content, add mcpServers alongside what is there — do not replace the file. A config with other settings should end up looking like this, with your existing keys untouched:

{
  "coworkUserFilesPath": "...",
  "preferences": { "...": "..." },
  "mcpServers": {
    "screaming-frog": {
      "command": "/Users/you/.local/bin/uvx",
      "args": ["screamingfrog-audit-mcp"]
    }
  }
}

Then quit Claude Desktop completely and reopen it — it reads that file only at startup, and closing the window is not enough. On macOS use Cmd+Q. The server then appears under the tools icon in the chat box.

ChatGPT desktop app (Codex)

The ChatGPT app bundles Codex and reads the same ~/.codex/config.toml, so the command above configures both. Nothing extra to do — restart the app and the tools appear in Codex.

ChatGPT on the web or mobile cannot use this server. Those connectors call a remote HTTPS endpoint, and this server is a local process that drives the Screaming Frog installed on your machine. It has to run where the Spider is.

Hermes

hermes mcp add screaming-frog --command uvx --args screamingfrog-audit-mcp

It connects, lists the tools it found, and asks which to enable — answer Y for all 14. Confirm with hermes mcp list, then start a new session. The entry lands in ~/.hermes/config.yaml, which you can also edit directly:

mcp_servers:
  screaming-frog:
    command: uvx
    args:
      - screamingfrog-audit-mcp
    enabled: true

Cursor

Settings → MCP → Add new global MCP server, or edit ~/.cursor/mcp.json directly. Same shape as Claude Desktop:

{
  "mcpServers": {
    "screaming-frog": {
      "command": "uvx",
      "args": ["screamingfrog-audit-mcp"]
    }
  }
}

VS Code (Copilot)

.vscode/mcp.json for one workspace, or run MCP: Open User Configuration for every workspace. VS Code uses servers, not mcpServers:

{
  "servers": {
    "screaming-frog": {
      "type": "stdio",
      "command": "uvx",
      "args": ["screamingfrog-audit-mcp"]
    }
  }
}

Any other MCP client

It is a standard stdio server: whatever the config shape, the command is uvx and the argument is screamingfrog-audit-mcp.

The one requirement is that the client launches local processes on the machine where Screaming Frog is installed. Clients that only accept a remote HTTPS endpoint cannot drive a local crawler, whatever the config says.

Optional settings

Add these to the env block of any config (a [mcp_servers.screaming-frog.env] table in Codex):

Variable What it does
SCREAMING_FROG_PATH Path to the SEO Spider executable, if it is installed somewhere non-standard
SF_MCP_AUDIT_DIR Where crawl folders are written (default ~/.screamingfrog-audit-mcp/audits)
SF_ALLOWED_DOMAINS Comma-separated domains this server may crawl. Set it for anything unattended
{
  "mcpServers": {
    "screaming-frog": {
      "command": "uvx",
      "args": ["screamingfrog-audit-mcp"],
      "env": {
        "SF_MCP_AUDIT_DIR": "/Users/you/audits",
        "SF_ALLOWED_DOMAINS": "example.com,acme.co.uk"
      }
    }
  }
}

First run

Ask your client: "check my screaming frog install". It calls check_install, which reports the binary it found, your licence tier, and what that tier can do.

If the server won't start

An MCP server talks over stdio, so a startup failure shows up in your client as a dead server with no reason given. Run the preflight in a terminal instead:

uvx screamingfrog-audit-mcp --doctor

It checks your Python version, the MCP SDK, whether the SEO Spider is found and actually runs, which command-line options your build supports, your licence tier, and whether the audit folder is writable — then prints a config matching how this copy was installed.

  [PASS] Python: Python 3.12.7 on Darwin
  [PASS] MCP SDK: MCP SDK 2.1.1, using MCPServer (mcp 2.x)
  [FAIL] SEO Spider: Screaming Frog SEO Spider not found
    Install it from https://www.screamingfrog.co.uk/seo-spider/ ,
    or set SCREAMING_FROG_PATH to the executable.

Common causes: uvx not on the client's PATH (use an absolute path to uvx, which which uvx will give you), or the config edited but the app not fully restarted.

The free-tier situation

The received wisdom is that the Screaming Frog CLI needs a licence. It does not. Verified against a build reporting Licence Status: Missing:

Works unlicensed --headless, spider / list / sitemap crawl modes, every tab export, every saved report, sitemap generation
Licence-gated save/load crawl, crawl comparison, config files, JavaScript rendering, scheduling, and the GA4 / Search Console / PageSpeed / Ahrefs / Moz integrations
Capped 500 URLs per invocation — not per site

Because the cap is per invocation, start_crawl(full=true) discovers URLs from robots.txt and the sitemaps, batches them under the cap through list mode, and merges the exports back into one set. That crawls a site of any size on the free tier.

A licence removes the cap and makes full unnecessary. Everything else works the same.

Tools

Tool What it does
check_install Install status, licence status, current limits, and how to fix a failed lookup
available_filters The export names your Screaming Frog build accepts
start_crawl Background headless crawl. full beats the free cap, everything exports every table
crawl_status Poll a running crawl. Omit job_id for the most recent
cancel_crawl Stop a crawl, keep partial exports
list_crawls Crawl folders, newest first, with headline counts
get_issues The priority-ranked issue register. Start here
get_analysis What the set of URLs means: depth, link equity, sitemap accuracy, content depth, performance, indexability, duplication
list_exports The CSV exports in a crawl, with row counts
read_export Rows from one export: column-selectable, paged, capped, filtered by contains / exact / regex on any column
aggregate_export Counts and group-by without returning rows — "how many 404s", "status codes by folder" — in one small response
storage_summary Disk used per saved crawl, largest first
delete_crawl Permanently delete a crawl folder (requires confirm)
build_report The branded deliverable: audit-workbook.xlsx (Summary, Issue register, Analysis, Data index, and every export as its own highlighted sheet), a printable report.html, report.md and analysis.json. consolidate=True folds the CSV exports into the workbook and deletes them, leaving one file

Two design decisions worth knowing

Crawls are background jobs. A crawl takes minutes; an MCP call should answer in seconds. start_crawl forks a detached child and hands back a job_id. Nothing blocks unless you pass wait_seconds. The crawl survives the MCP server restarting.

Reads are capped, on purpose. A finished crawl folder is tens of megabytes of CSV. Feeding that to a model is both useless and expensive. Every read tool caps at 500 rows, lets you pick columns, and truncates long cells. Ask get_issues first — it's the whole site in about 60 lines — and aggregate_export when the question is "how many" or "broken down by", since counting rows by hand through a model is the expensive way to get a number. Reach for read_export only when you actually need the rows.

The deliverable

build_report writes four files into the crawl folder:

File What it is
audit-workbook.xlsx The master workbook. Summary, Issue register, Analysis, Data index, and every crawl export as its own sheet — around 70 tables on a full crawl
report.html Printable summary. Open it and Print to PDF
report.md The same content as plain text
analysis.json The derived layer, machine-readable

Every sheet has a frozen header, autofilter, banded rows, sized columns and a coloured tab. Cells are highlighted where the value is the finding — issue priority, 4xx/5xx status codes, non-indexable URLs, thin content, slow responses — so the problems are visible before you read a cell.

Reports carry a credit line naming the tool and its author.

One workbook instead of seventy CSVs

A finished crawl leaves around seventy exports in the folder, and the workbook already carries every one of them. build_report(consolidate=True) folds them in and deletes them, so the folder holds the workbook, the report files, and a consolidated.json manifest naming which sheet holds which table.

The delete is earned. Each sheet is written, the saved workbook is reopened from disk, and every sheet is checked against the row count it should hold. Only then is a file removed. If the save fails, the reopen fails, or a sheet comes back short, nothing is deleted and the reason is reported. An export too large to carry in full is kept on disk and named in the manifest, because a sampled sheet is not a substitute for the file.

It is off by default: read_export and aggregate_export read those CSVs. Turn it on when the folder is a finished deliverable rather than a crawl you are still asking questions about. Those tools then explain the consolidation and point at the workbook instead of reporting the folder as empty.

Where crawls are stored

~/.screamingfrog-audit-mcp/audits/<label>/ by default. Each folder holds the raw Screaming Frog CSV exports, audit-summary.json, and whatever build_report wrote — or, after a consolidated report, the workbook and manifest in place of those exports.

Override with SF_MCP_AUDIT_DIR:

{
  "mcpServers": {
    "screaming-frog": {
      "command": "uvx",
      "args": ["screamingfrog-audit-mcp"],
      "env": { "SF_MCP_AUDIT_DIR": "/Users/you/audits" }
    }
  }
}

Set SCREAMING_FROG_PATH if the Spider is installed somewhere non-standard.

Restricting what it may crawl

By default this server will crawl any host it is asked to. That is fine on your own machine, and a liability when an agent runs unattended: a confused or prompt-injected one can point a crawler at internal addresses or at third parties who did not ask to be crawled.

Set SF_ALLOWED_DOMAINS and start_crawl refuses anything else:

"env": { "SF_ALLOWED_DOMAINS": "example.com,acme.co.uk" }

Subdomains of a listed domain are allowed; look-alikes are not, so shop.example.com passes and example.com.evil.com does not. --doctor reports whether an allowlist is active.

Environment variables

All three are listed with examples under Optional settings in the install section.

Use it without MCP

The crawl pipeline is a plain module:

python -m screamingfrog_audit_mcp.runner --url https://example.com --output ./audit
python -m screamingfrog_audit_mcp.runner --url https://example.com --output ./audit --full

Gotchas found the hard way

  • An unknown command-line flag aborts the whole crawl, it is not ignored: FATAL - SeoSpider failed to start ... UnrecognizedOptionException. The option set differs between versions — --skip-empty does not exist in 19.8, for instance — so this server reads the binary's own --help and passes only what your build advertises. Works on old and new versions alike.
  • One wrong filter name aborts the whole crawl. Screaming Frog renames tab filters between versions, and an unrecognised name fails the run with a Java stack trace rather than skipping it. Every name is validated against your installed binary at crawl time, so an upgrade degrades instead of breaking.
  • Its own --help output contains a poisoned entry. The binary lists a placeholder UNDEF:Unknown, and passing it back aborts the crawl with Using UNDEF as tab is not supported. It's filtered out.
  • os.kill(pid, 0) is not a liveness probe on Windows. Any signal other than CTRL_C/CTRL_BREAK routes to TerminateProcess, so the usual "does this pid exist" idiom would kill the crawl and then report it finished. Windows uses tasklist to check and taskkill to cancel, and never signals. Detaching differs too: start_new_session is POSIX-only.
  • everything mode is curated, not literal. The Spider lists ~1,150 tab filters, but 800+ are Custom Extraction / Custom Search / Custom JavaScript / AI filters that need a licence-gated config file and are permanently empty. Requesting them costs minutes and returns nothing, so those groups plus the API-dependent ones are excluded.

Development

git clone https://github.com/mshahiddigital/screamingfrog-audit-mcp
cd screamingfrog-audit-mcp
pip install -e ".[dev]"
pytest

The test suite runs on synthetic export fixtures, so it passes on a machine that has never had Screaming Frog installed.

Changelog

See CHANGELOG.md.

License

MIT. Not affiliated with or endorsed by Screaming Frog Ltd. You need your own copy of the SEO Spider; issue names, descriptions and fix guidance in the output are Screaming Frog's own.

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