Squirrelscan vs Submit Map
A side-by-side look at the Squirrelscan and Submit Map MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Squirrelscan for marketing work over a hosted endpoint; choose Submit Map for marketing over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Squirrelscan when
- You need dedicated capabilities in the Marketing domain.
- You prefer a remote HTTP/SSE transport.
- You want tools like
run_audit, get_audit_status, list_audits.
Choose Submit Map when
- You need dedicated capabilities in the Marketing domain.
- You prefer a remote HTTP/SSE transport.
- Its auth model fits you: API key required.
- You want tools like
search_platforms, get_platform, qualify_project.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Marketing | Marketing |
| Quality signal | 63/100 · Good | 64/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Remote HTTP/SSE | Remote HTTP/SSE |
| Auth | Not declared | API key required |
| Pricing | Not declared | Free |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 101 | 265 |
| Directory activity | 0 views 0 installs 0 upvotes | 4 views 0 installs 1 upvotes |
| Tools | 27 | 11 |
| Full listing | View Squirrelscan | View Submit Map |
Tools & capabilities
Squirrelscan tools 27
run_auditRun a cloud audit of a website (crawl + 300+ rule analysis + report). Credits are spent as the audit runs (pay-as-you-go). The dry run is optional: pass confirm: true on the first call to start straight away. Without confirm, an audit whose estimate is over the org's auto-run threshold comes back as status "confirmation_required" with the estimate to show the user; one at or under the threshold just starts. That response carries "sufficient": true means the organization can pay, so show the estimate and call again with confirm: true; false means it cannot, and the response then carries the cost, the balance, the credit reset date and an upgrade_url for that organization. Relay those, and do NOT retry with confirm: true, which is refused. Pick the audit with level: quick (25 pages from the seed and sitemaps with external link checks, without the cloud checks), surface (100 pages, one per URL pattern, with the cloud checks and external link checks) or full (500 pages, every page it can reach; Pro and Team only: on the Free plan a full request crawls one page per URL pattern instead, up to the plan's page ceiling, and says so in level_notice). Without level the website's own level applies (a new website starts on surface). Every level checks external links, quick included, unless the website's external link setting or this run's external_links turns them off; each distinct external link the cloud verifies costs 1 credit (a link it cannot verify costs nothing), at most one per page of the page budget, and the estimate includes it. Use max_pages to size the crawl (max_pages: 1 audits just the entry URL, the cheapest run). Audits are asynchronous and take minutes: poll get_audit_status with the returned run_id, then fetch results with get_report. The website is registered automatically on first audit. A started run carries a schedule field describing the site's recurring audits: when state is active say so, since each of those runs costs credits, and settings_url is where the user turns them off. pending_first_audit: true means they switch on by themselves after this site's first successful audit, estimated_cost is the most they spend per run, week and month, and update_website_settings with schedule "off" turns them off.get_audit_statusPoll a running audit by run_id (from run_audit or list_audits). Status queued/pending/running means keep polling (every 15-30 seconds): the response includes a progress field (phase, message, page/link counts) when available. Status queued means cloud audits are busy and the run is waiting for a slot: it starts by itself, and its queue field gives its position, a rough eta_minutes (null when unknown) and a message to pass on. Do not start the audit again. Status completed means the report is ready: call get_report with the same run_id. Status failed/cancelled includes the error and completion reason. A failed run also carries failure_reason_code (one of dns, tls, connection, timeout, http_4xx, http_5xx, redirect, robots, audit_timeout, stalled, unknown) and failure_next_step, so you can act on the cause rather than parsing the error sentence, plus failure_diagnostics: attribution (target_site, squirrelscan, mixed or unknown; never guess past it), category, stage, the observations that support it, what remains uncertain, and the bounded list of fetch attempts; legacy is true when the run predates recorded evidence. A cancelled run has none of these, because it was stopped rather than defeated by the site. Once the run has a report, health_score and issues_found are read from that published report, so they equal get_report's summary.healthScore and its failed+warnings (#1700). health_score is null for a blocked or unreachable site: that audit has no meaningful grade. A completed run also carries a schedule field describing the website's recurring audits: state is off, active, capped, unschedulable or paused, cadence_label reads as a sentence, settings_url is where the user changes the cadence or turns it off, and cap says how many scheduled sites the plan funds and how many are spent. estimated_cost is the most those runs spend per run, week and month. Recurring audits turn on by themselves after a site's first successful audit and each run costs credits, so pass that on rather than leaving the user to discover the charge.list_auditsList the organization's audit runs: currently active (queued/pending/running; queued means waiting for a free cloud slot, and it starts by itself) plus recent runs of any status. Pass website_id (from list_websites) to get one website's full audit history, oldest runs included, and page through it with limit/offset using the returned total/has_more. This is the way to reach the preserved reports of a soft-deleted website: its runs still list under its old website_id. total/has_more describe the `recent` array only, and `recent` already includes any queued/pending/running run, so `active` is a live view of those same runs and not extra items to add to the count. Use the run ids with get_audit_status or get_report, and website ids with list_issues. Numbers on a recent run come from its published report (#1700): health_score is that report's overall score (the same value as get_report's summary.healthScore; null when the site was blocked or down, which earns no grade) and issues_found is the report's failing + warning checks (its summary.failed + summary.warnings). health_score is the metric to compare run over run: it is the only one rescored consistently across the whole site. Do NOT compare issues_found with the `open` count from list_issues: the issue tracker folds a rule failing on many pages into one open issue and carries issues forward until they are re-checked, so its count is legitimately much smaller and moves independently.list_websitesList websites the organization has audited, with their latest run status, health score, and owned/prospect kind. Each row carries last_run_id (the latest run, any status) and last_report_run_id / last_report_id (the latest completed run whose report has not been deleted). Pass last_report_run_id to get_report to read a website's newest report without knowing a run id in advance, or list_audits with website_id for its full history. Use the website_id with list_issues/get_issue. Websites registered but never audited do not appear; run_audit or add_website registers a new one. Ephemeral one-shot audits never appear. Returns total/has_more for pagination. Filter by kind to separate sites the user runs from one-off prospect audits: kind: "prospect" returns ONLY sites explicitly marked as such, so it is the safe way to build a bulk-delete list.add_websiteRegister a website with the organization without running an audit (run_audit registers automatically, so this is only needed to set a site up ahead of time). Returns the website_id; idempotent per domain, so calling it again returns the existing website. Pass kind to classify it as owned or prospect up front. On a plan with scheduled audits, a NEW site is registered with recurring weekly audits already on, and each of those runs costs credits: tell the user before calling this; update_website_settings with schedule "off" turns them off. The result's scheduled_audits field reports what was actually set.delete_websiteDelete a website from the organization (soft delete: past audits, reports, and issues are preserved, and published report links keep working). Frees a slot under the plan's website limit. Re-adding the same domain later registers a fresh website with a new website_id. Call once without confirm to see what will happen; call again with confirm: true to delete. To remove many sites at once, use delete_websites.delete_websitesDelete up to 50 websites in one call, for cleaning up a dashboard that has filled with one-off or prospect audits. Same soft delete as delete_website (past audits, reports, and issues are preserved, published report links keep working, slots are freed) and the same two-step confirm: call once without confirm to see the domain behind every id, then again with confirm: true. EVERY result echoes the domain, so read them back to the user before and after: an id is not a name, and this is the tool most likely to be pointed at the wrong list. The preview also shows each site's kind and an owned_count: unclassified sites read as owned, so an 'owned' entry in a list you built from prospects is the clearest sign the wrong ids were assembled. Ids that do not resolve are reported per-id, never as a whole-call failure. To pick the ids, list_websites with kind: "prospect" returns only sites explicitly marked disposable.get_website_settingsRead one website's stored audit settings: its audit level (quick, surface, full or custom) with the page cap, crawl strategy, rendering and external link checks it sets, the crawl depth, crawl scope, include/exclude patterns and internal link checks, whether broken link alerts are on (broken_link_alerts, Pro and Team), and its recurring-audit schedule. runs_as is how the next audit runs on the organization's plan (a level or page cap the plan does not run is held to the plan there, with a notice) and credits_per_run_max is the most one audit of it can cost. schedule says whether recurring audits are on; pending_first_audit: true means they switch on by themselves after the site's first successful audit, and estimated_cost is the most they spend per run, week and month.update_website_settingsChange one website's stored audit settings: level, max_pages, render, external_links, max_depth, scope, include_patterns, exclude_patterns and internal_links, broken_link_alerts (Pro and Team; switching it off is allowed on every plan), and schedule (off, daily, weekly or monthly) for its recurring audits. Omitted fields are left unchanged. Values are checked the same way the dashboard's settings are and held to the organization's plan; the result reports what is stored afterwards, which fields were applied, and any plan clamp. Turning recurring audits on, changing their cadence, or a change that raises the most one audit can cost returns status "confirmation_required" with the estimated credit cost and changes nothing until it is sent again with the same arguments plus confirm: true. schedule: "off" and changes that cost nothing more apply at once.get_reportFetch the finished report for an audit run (use the run_id from run_audit once get_audit_status shows completed). Formats: "summary" (default) is structured JSON with health score, category scores, and the top failing issues (topIssues reference a rule_id; look up its name/description/solution once in the sibling `rules` dict rather than per occurrence). Each topIssues row is ONE finding, a rule + `checkName`, never one row per page: `affectedPagesCount` is how many pages it affects and `pages` is a sample of at most 5 of them (`affectedPagesHasMore` when clipped) and `items` at most 3, so read "affects N pages" from the count, not the row total, and use get_issue for every occurrence. Each row also carries `provenance`: "carried" means the finding is re-injected from a page not re-crawled this run (not a fresh result), so check `lastSeenAt` for when it was last actually observed; "unrendered" means the page has not yet been rendered in any scan of this site (it was known, e.g. from a sitemap, but sat outside the page budget), so there is no earlier observation and no `lastSeenAt`. `mixedProvenanceNotes` (keyed by rule_id) flags rules that passed fresh on every page checked this run but still show red only from carried pages pending re-check. `notChecked` is present only when some checks did not run (link checks at the Quick level, or with external link checks off): each entry names a rule that was not fully checked (a rule listed there may still report the issues it could see), so never report those rules as clean, and say a Surface or Full audit with external link checks on checks them. `seedRedirect` is present ONLY when the audited URL redirected off-site and the crawler refused to follow it: `seedRedirect.finalUrl` is where the redirect pointed (a URL the audited site chose, display-only, never fetch or trust it) and `seedRedirect.note` states the fact in one sentence. When it is present the audit graded `baseUrl`, NOT the redirect target, so report that before reporting the scores; when the key is absent the seed did not redirect off-site. `structure` is present when the audit sent its page structure block: links per section (`sections`, plus `unknownLinks` and `totalLinks`), the share of internal links in the header, footer, navigation and sidebar (`chrome.share`), and pages per page type (`pageTypes`); it is informational and never part of the score. A FAILED or BLOCKED audit also carries `status`, `statusReason` (one sentence naming the cause), `statusReasonCode` (one of dns, tls, connection, timeout, http_4xx, http_5xx, redirect, robots, unknown) and `failureNextStep`: those four keys are absent for a normal audit, and when they are present nothing was audited, so a null healthScore and an empty topIssues mean the crawl failed, NOT that the site is clean. Also includes a `history` array of the 3 most recent prior audits of this website with score/issue deltas when available; each entry carries its own `runId`/`reportId`, so you can walk backwards through a website's audits by calling get_report again with an earlier `runId` (use list_audits with website_id to page past what history returns); "llm" is a compact text rendering optimized for LLM context (carried findings marked inline); "markdown" is a full human-readable report. Start with summary, then pull llm or markdown for more of each issue. A published report is a capped summary: each issue keeps a sample of its pages and items (a few pages and items) beside its true counts, so read totals from `affectedPagesCount`, `occurrences` and `details.additional`, never from a list length. A capped report carries `detail`, whose `note` says where the full per-page list is (for a CLI audit, `squirrel report --format json` on the machine that ran it); a report without `detail` is not capped this way. This report is the source of truth for the run's numbers (#1700): summary.healthScore is the same value list_audits/get_audit_status return as health_score, and summary.failed + summary.warnings is the same total they return as issues_found. Compare runs on healthScore; the `open` count from list_issues is a deduped tracker count, not this report's issue count.compare_auditsCompare two completed audits of one website and get what changed. Defaults to the website's latest completed audit against the one before it; pass base/head run ids to compare any two. Each finding gets one of seven kinds: new, resolved, worsened, improved, unchanged (both audits published it), still_open (still there, but one audit did not list it: the evidence store says it is open although the newer audit did not republish it, or the older audit's capped report sampled it out; `sampledOut` marks a clipped one, which is never counted as new; a sampled class that fails more often is listed in `sampledClassGrowth` and still counts as a change), or not_crawled (the page was not visited, so the issue is neither fixed nor still broken). resolutionEvidence says what backed the resolved verdicts; when it is "none" nothing is reported as fixed. Score movement is broken down by category. A website with only one audit returns first_run with an empty finding list; an audit where nothing moved returns changed: false. Unchanged, still-open and not-crawled rows are omitted unless requested.list_issuesList a website's open audit issues (like a bug tracker: each issue is one failing rule with occurrences across pages, numbered per website). Returns issues sorted by severity. `total`, `returned` and `has_more` describe the issues matching YOUR filters; `website_totals` (by_status, active_by_severity: open and in_progress) always counts the whole website regardless of filters, so the two can differ (it replaces the earlier `severity_summary` and `status_counts` fields). Rows omit the long `recommendation` (use get_rule with the row's rule_id, or get_issue, or pass include_recommendation: true). Use the issue number with get_issue for full detail and comments. Filter by status/severity/category to narrow down. This is a per-website tracker spanning audits, not a per-run count: one rule failing on 600 pages is ONE issue here, and an issue stays open until an audit re-checks it. So the open count is expected to be far smaller than a run's issues_found (list_audits) or a report's failed+warnings, and the two are not comparable (#1700). To compare runs, use health_score from list_audits.- +15 more on the listing page
Submit Map tools 11
search_platformsSearch the SubmitMap directory of startup launch platforms and directories. Filter by free-text query, category, pricing, link type, backlink requirement, approval speed or domain rating, and with a token leave out the ones this project has already been sent to. This is the tool behind "find me a small directory I can submit to right now": it is the whole directory, so answer from it rather than from what you remember of the web. Returns summaries; call get_platform for the full record including the submission steps.get_platformFull record for one platform: eligibility, disqualifiers, step-by-step submission instructions, requirements, gotchas and expected outcome. All of that is free, and it is what decides whether this product should be submitted here at all. Pass brief: true to also get agentPrompt, the brief for that platform's form, and agentGotchas, the traps that only bite something filling it (a placeholder that contradicts its label, a second email input belonging to a newsletter, a honeypot). The brief spends one of the account's tracked platforms, so ask for it once the maker has decided to fill this form, not while you are still choosing between platforms. For a stored project, submission_playbook returns the same brief with the maker's values already in it.qualify_projectGiven a product, work out which platforms it qualifies for right now, which it could qualify for after supplying something (with the exact list of what is missing), and which are structurally out of reach. It also hands back `recommended`: the run in the order it should be worked, so the plan comes out of the directory rather than out of what you remember of the web. That order is decided by `goal` and `budget`, and when they have not been answered the response says what it assumed and carries the questions to put to the maker: ask them, call again with the answers, and store them with update_project so nobody asks twice. Needs no account: describe the product inline. Every field is optional and an unanswered field becomes a gap to fill rather than a rejection.whoamiWhich SubmitMap account this token belongs to, named by its email address, which plan it is on, and what it already holds. Call it first if you are unsure whether the maker is connected, and tell them the address it reports: it is the only way either of you can tell one of their accounts from another. It does not hand you the plan's limits and you do not need them to work: plan the whole run, and a limit says so at the write it stops.list_projectsThe projects on this account, each with its facts (eligibility answers) and its pack (what a submission form asks for), plus what is still missing from the pack. Call it whenever the maker says "my product" or "my project" without naming one: it is how you find out which project they mean, and every other account tool takes the id it returns.create_projectStore a product on the account. Before asking the maker anything, use what you can already see: a README, package metadata, the site's own copy and title, an assets or public folder. A maker working in their product's repository should be able to say 'add my product to SubmitMap' and get a filled-in project back, with questions only about what is genuinely not there. Fill in as much as you can, leave the rest, and come back with update_project. Facts drive what it qualifies for; the pack is what you will paste into forms later. Ask about images early: most platforms want a square logo and many want a cover, and every asset in the pack is two fields, the public address (logoUrl) and the file on the maker's machine (logoFile), because a form uploads the file and only the address can be shown back to them.update_projectFill in or correct a stored project. Facts and pack are merged into what is there, so you can add one field at a time as the maker answers.submission_playbookEverything needed to submit a stored project to one platform, yourself, in the maker's browser: a preflight of what is still missing, the sign-in plan (on the first submission it carries a question for the maker: hand every login back to them, or use the Google address they write out, which you then pass back as signInAs), the pack values mapped onto the fields the form asks for, the steps, the gotchas, the agentGotchas (traps in the form itself), and the call to make afterwards. Read the preflight before opening a tab. One brief is out at a time per project: ask for the next platform only after record_submission has answered this one, because until then this tool refuses the next brief and names the one still open. Do not fetch briefs ahead or in parallel. This is the tool the free plan meters: it covers the same submissions the dashboard tracks, plus any platform the account has already sent to, and past that it says so and points at the upgrade rather than answering.record_submissionLog what happened to the dashboard: the listing URL, when it was sent, when it goes live. Call it as soon as a submission lands, before you ask for the next brief, including when it is only queued for review, and including when you are not sure it landed: that is what `attempted` is for. The next brief on this project is refused until this call is made. A platform that needs the maker (a captcha, a login, a payment, a file, an address to confirm) is recorded as `planned` with a note saying what you need from them: that hands it back without claiming an outcome, and frees the run to carry on. If the live platform did not match what the brief said, put the difference in `differsFromRecord`. This costs nothing on any plan and no status costs more than another, so record what actually happened: the brief was what spent the tracked platform, and leaving the row wrong now only makes the run harder to follow.plan_submissionsWrite the run order for a project: which platforms, in what sequence, and why each one is where it is. Anything already submitted to is dropped from the plan and named back to you in `alreadySubmitted`, because a plan is what is still ahead. Pass the platforms in the order they should be worked, with a short reason on each, plus a summary of the strategy. The plan appears on the maker's dashboard as a checklist that ticks itself off as submissions land. Anything already tracked is reordered rather than reset. Call it after qualify_project, using the `recommended` list it hands back, and if that response carried `questions`, put them to the maker before you plan: the order depends on the answers, and a plan written on an assumption is one they have to undo by hand. A plan costs nothing on any plan, so plan the whole run the product deserves rather than a short one sized to a guess about what the account can track.list_submissionsWhere every submission for a project stands: what went out, when, what came back, and what is still waiting. This is the tool behind "check my submissions", "what did I submit", "did I ever submit to that one" and "how is my launch going", so answer those from here instead of asking the maker to remember. Start with list_projects if they have not named a project.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Squirrelscan
{
"mcpServers": {
"squirrelscan": {
"url": "https://mcp.squirrelscan.com/mcp"
}
}
}
Submit Map
{
"mcpServers": {
"directory-3": {
"url": "https://submitmap.com/api/mcp"
}
}
}
Frequently asked questions
Squirrelscan is categorized under Marketing and uses a remote HTTP/SSE transport. Submit Map belongs to Marketing and uses a remote HTTP/SSE transport. Pick Squirrelscan for marketing work and Submit Map for marketing.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Squirrelscan has no declared pricing — check the project's own site. Submit Map is listed as free. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add squirrelscan and directory-3 as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Squirrelscan has a quality signal of 63/100 (Good) with 0 views, 0 installs and 101 GitHub stars. Submit Map has 64/100 (Good) with 4 views, 0 installs and 265 GitHub stars.