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510,057 tools. Updated 2026-09-03 20:54

"A server for finding Google Sheets information and resources" matching MCP tools:

  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
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  • Which export destinations this account has connected (Close, GoHighLevel, Google Sheets) and whether each is ready to receive leads. Check this BEFORE export_leads or create_automation with a CRM destination — those fail if the integration isn't connected, and Close additionally needs one manual export first to save its field mapping. File destinations (csv/xlsx/json) always work and need nothing connected.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Extract structured transaction data from a contract at a URL. Downloads the document, extracts text (with OCR fallback for scanned PDFs), and runs PrimaCoda's contract-extraction prompt to return parties, addresses, dates, prices, and key contract fields. Use this when an agent has the contract hosted somewhere (Dropbox, Google Drive direct download, Square Space, etc.) and wants to skip the upload step. For multi-document deals (purchase + addenda + disclosures), use the PrimaCoda dashboard's batch upload — this tool handles ONE document. Args: pdf_url: Direct download URL for the contract (PDF, DOCX, TXT, or image). Must be reachable from the PrimaCoda server. Google Drive "shared link" URLs work if set to "anyone with link"; other share URLs may need their direct-download form. api_key: Your PrimaCoda MCP API key (starts 'pck_').
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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  • List supported Google Maps place type values for search filters. Returns place_types as a string array. Use a value with place_type on google-maps.search or google-maps.nearby_search. Cost = 1 token.
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Matching MCP Servers

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  • Produce a deterministic remediation REQUEST bundle (rubric + fix schema + per-finding metadata + fingerprints) for YOU (the host agent) to fix. This tool calls no model and needs no key. For each finding, propose the corrected FULL file content, then VERIFY with verify_fix and keep only fixes that clear the finding. Never touch files with secrets; never auto-merge. Pass 'findings' from scan_path --format json.
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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  • Get Lenny Zeltser's expert writing guidelines for security reports and assessments. Provides guidance on tone, structure, clarity, executive summaries, and avoiding common writing mistakes. Includes rating-sheet items (the four lens sheets: structure, look, words, tone) as concrete reference points for grounded feedback. Works for any security document. This server never requests your documents and instructs your AI to keep them local—guidelines flow to your AI for local analysis. Note: For incident response reports specifically, use the ir_* tools which provide deeper section-by-section review criteria.
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  • Get Lenny Zeltser's cybersecurity-writing rating sheet(s) so your AI can apply the rubric. Returns the structured rubric (groups, items, scoring bands) WITHOUT computing a score. Use `rating_score_writing` if you also want a numeric score, gap analysis, or rubric-anchored feedback. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Get Lenny Zeltser's one-page Vulnerability Advisory Brief template. Covers Bottom Line, Quick Facts, Are We Affected?, Defensive Actions (with What/Why/When/Who), What We Don't Know, and More Information. This server never requests your vulnerability notes and instructs your AI to keep them local—the brief template and guidelines flow to your AI for local analysis.
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  • Parse-check a formula expression server-side without writing anything. Returns { ok, error?, rewrittenFormula?, referencedFunctions, unknownFunctions }. Use BEFORE update_row / create_row when the formula references functions or syntax you're not 100% sure of: a `=SUMIFS(...)` with the wrong arg order or a misspelled `=AVERAG(...)` will round-trip into the cell as a stored carrier with no value, and the user will see #NAME? or #VALUE? on next view. Catch it here. `unknownFunctions` flags any identifier that isn't in the Dock Sheets catalog (including likely typos); `referencedFunctions` lists the canonical post-alias names the engine will see. Cheap, public, no auth, no workspace context needed.
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  • Get annual and quarterly balance sheets for a symbol (e.g., "AAPL"). Returns total assets, liabilities, equity, cash, and debt. Needs your own PAID Alpha Vantage key via _apiKey — Pipeworx fronts no key for this pack and a free-tier key is refused when the call goes through the gateway (Alpha Vantage meters its free tier by source IP, not by key). Keyless alternative for US company financials: sec-xbrl.
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  • Get comprehensive information about a specific dealership. Returns Google-enriched dealer knowledge optimized for assistants: • Name, address, phone, website • Google rating, review count, hours, business status • Inventory count and OpenDealer profile links • Contact points for sales / customer service Use this when a shopper asks "tell me about X dealership" or needs hours/ratings for a known dealer. Prefer a slug from dealers_near or search results. CRITICAL: Only use URL fields from the response (website, urls.*). NEVER invent or construct URLs.
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  • Get the available services, prices, durations, and bookable staff or resources for a specific Korean beauty or wellness shop. Use this after finding a shop when service details, prices, durations, staff, or resources are needed before checking appointment availability. Pass lang to receive the content translated into the customer's language.
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  • Follow a URL's HTTP redirect chain and audit response security headers (CSP, HSTS, X-Frame-Options, COOP, CORP, COEP, Permissions-Policy), grading A+ to F and flagging information leaks such as server-version disclosure. Use this for HTTP-layer/header posture. Use ssl_check instead for certificate or TLS-handshake issues, or security_scan for a full domain report. Read-only (an HTTP GET-style probe that sends no payload); requires no API key; rate-limited. Returns a text report: grade, header findings, redirect trace, issues, and actions.
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  • POST-ACTION Wallet Secret Guardian ($0.02). Scans for BIP-39 seed phrases (12 or 24 consecutive wordlist words), raw hex or WIF-format private keys, Ethereum/Bitcoin wallet addresses, and API keys/bearer tokens appearing near wallet/custody/signing terminology. Any finding results in NO_COMMIT — wallet secrets have no safe threshold, unlike other DCL evaluators. Returns a `sanitized_output` with all matches redacted (null if nothing was found) and a masked `redacted_sample` per finding — the real value is never returned or stored server-side.
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  • Get Lenny Zeltser's scoring playbook so your AI can score a draft locally against a cybersecurity-writing rating sheet. THIS IS THE ONLY TOOL THAT PRODUCES NUMERIC SCORES — the writing-coach tools (`get_security_writing_guidelines`, `ir_*`, `product_*`) never score. Returns the rubric plus step-by-step instructions for applying it. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Find outliers and anomalies in structured data — ideal as a second step after pulling records from Google Sheets, Airtable, Supabase, Notion databases, HubSpot, Financial APIs, GitHub, NPM, or any source that returns rows of JSON. Fully stateless: send known-good rows as training and suspect rows as test in ONE call. Returns per-row anomaly scores, confidence levels, and the top features explaining WHY each row was flagged. Typical workflow: (1) Pull data from another tool (e.g. Google Sheets, Supabase query, HubSpot deals). (2) Pass the first N rows as training (normal baseline). (3) Pass remaining or new rows as test. (4) Report which rows are anomalous and why. Works on JSON objects, numbers, text, arrays. No separate training step required. Examples: - Spreadsheet QA: Pull 500 sales rows from Sheets → train on first 400 → test last 100 → flag outlier entries - Financial screening: Get ratios for 50 stocks from a financial API → find anomalous ones - CRM hygiene: Pull HubSpot deals → flag deals with unusual discount/value patterns - Dependency audit: Get NPM package metrics → flag packages with anomalous quality scores - Commit review: Pull GitHub commit metadata → flag unusual commit patterns
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  • Answers ONE question: whether stress is reaching US HOUSEHOLD balance sheets — not firms (corporate_transmission_board), not banks (failure_radar_board), not money-market plumbing (the Seiche sibling server). Read the Household Credit board: is stress transmitting through US household balance sheets? From free public data (FRED keyless): Fed quarterly delinquency and charge-off legs (card, consumer, mortgage, card charge-offs — level vs each leg's own trailing decade AND the yoy direction; falling never scores), G.19 revolving-credit velocity (two-sided — both tails historically meant stress), and the debt-service ratio as unscored context. The transmission thesis runs household -> corporate -> institution: this board confirms what the funding boards lead. Channels that cannot be read are listed in cannot_see, never reported as calm. Display-only: feeds no institution score and no watchlist tier. Returns ~4KB slim by default; pass full:true for thresholds, method prose and full sparklines.
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