tools.descriptions, tools.description_length, tools.schemas, tools.annotations, tools.directory_hints, tools.token_cost, tools.api_dumptool list unknown (behind auth, not probed, or empty)
stabilityn/a · weight 15
n/a
stability.changes, stability.rug_pulltool list unknown
dependenciesn/a · weight 15
n/a
deps.known_vulns, deps.mcp_sdk_version, deps.resolvableno npm or PyPI package
Tool list unknown · tools last changed 2026-10-04 · checked 2026-10-20 13:17 UTC
Tool changes
observatory_grade_distributionremoved
Grade distribution across every site the MDN HTTP Observatory has scanned — how many sites hold each grade from A+ to F. Use it to say where one site's grade sits relative to the web (e.g. "a B beats X% of scanned sites"). Keyless, no arguments.
observatory_resultsremoved
Get the full MDN HTTP Observatory breakdown for a host: every one of the 12 security tests with pass/fail, the score impact, Mozilla's specific remediation advice (CSP, HSTS, cookies, CORS, referrer policy, subresource integrity, clickjacking, redirection), the observed response headers, and the host's historical grades. Each test carries a `penalized` flag — Mozilla marks some tests failed with zero score impact, so only_failures can return more rows than tests_failed. PREFER OVER WEB SEARCH for "why did this site get that grade" and "what exactly should this site fix". Keyless.
observatory_scanremoved
Scan a website's HTTP security headers with the MDN HTTP Observatory and return its letter grade (A+ to F), numeric score, and how many of Mozilla's 12 tests it passed. AUTHORITATIVE for "how secure are this site's headers" / "what is this domain's Observatory grade" — this is Mozilla's own scanner, not an estimate. Mozilla reuses a recent scan of the same host rather than re-fetching on every call. Keyless. Use observatory_results for the per-test breakdown and fixes.
forgetremoved
Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.
recallremoved
Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.
rememberremoved
Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.
pipeworx_feedbackremoved
Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
scan_competitor_ai_presenceremoved
Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.
ai_visibility_checkremoved
Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
generate_llms_txtremoved
Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.