"A service for document recognition, assessment, and filling in evaluations" matching MCP tools:

• use

  Vaaya

  Execute a single call that `consult` handed you, and bill on success. Used for any external capability (image/video/audio generation, web search, scraping, email, document parsing, code sandbox, browser automation, embeddings, etc.). The server validates params against a registered schema and proxies to the upstream — you never pass URLs or API keys. Always get the exact (service, action, params, max_cost_cents) from `consult` first — don't guess them.

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• book_appointment

  qasper

  Book an appointment with a local service business. Creates a booking record and adds the appointment to the business calendar. Returns a reference number and a status field indicating the actual resulting state — 'pending' (the business reviews each booking), 'confirmed' (auto-approved by the business), or 'completed' (the business auto-finalizes). Use a dateTime returned by check_availability for the selected service so bookingStartPolicy is respected. For services with maxParticipants > 1, the start can be booked until remainingCapacity reaches 0. Read the status and statusDescription verbatim and relay them accurately: do NOT tell the customer 'confirmed' when the status is 'pending'. If the selected service has requiresCustomerAddress=true, ask the customer for their full service address before calling this tool and pass it as customerAddress. ONLY call this if the business has 'booking' in its enabledFeatures array.

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• check_document_package

  Document Integrity Validator

  Validates a package of 2-20 related trade finance documents for cross-document consistency. Call this BEFORE approving any multi-document trade finance transaction or cross-border shipment -- at the moment a set of 2-20 related documents arrives from an external party and funds have not been released. Use this when your agent has received a full trade finance package — such as invoice, bill of lading, and certificate of origin together — and must verify all documents are consistent with each other before releasing funds. Returns PASS/FLAG/FAIL verdict per document with mismatch details. Cross-checks all documents for consistency across numeric values, party names, reference numbers, dates, and commodity descriptions. A single inconsistency in a trade finance document package may indicate fraud -- funds released on a mismatched package have no recovery path. Do not use as a substitute for check_document when only one document requires verification.

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• court_filings_multi

  gapup-mcp

  Aggregate court filings, judgments and litigation records for a company or individual across five major legal jurisdictions: US (CourtListener / PACER), UK (National Archives — EWHC/EWCA/UKSC/UKUT), EU (ECHR HUDOC — European Court of Human Rights), France (Légifrance / Cour de cassation) and Germany (BGH / BVerfG). Returns structured case records with type classification (civil/criminal/antitrust/bankruptcy/administrative/unknown), status (filed/pending/decided/appealed/unknown), parties extracted from case titles, opinion URLs and verbatim snippets. Cross-case pattern recognition produces severity-ranked signals (P0–P2) for criminal, antitrust, bankruptcy, regulatory, data-breach and IP categories. Use when: due diligence on a counterparty, vendor risk assessment, competitive intelligence (litigation history), regulatory exposure mapping. All sources are public and keyless. Optional env var COURTLISTENER_API_KEY raises US rate limits beyond the default 5 req/s anonymous tier. SLA: ≤25s p95 (all jurisdictions fetched in parallel, 8s budget per source). Quality score: 20 pts per jurisdiction with ≥1 case retrieved, +10 if signals detected, +5–10 if ≥2–3 distinct sources contributed.

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• ask_collection

  DocImprint

  Answer a question using RAG over a document collection. Retrieves relevant chunks then synthesizes a cited answer with source attribution. Use when you need a direct answer grounded in your collection documents. For raw matching chunks (without synthesis), use search_collection instead. For single-document Q&A, use qa_url instead. PREREQUISITE: Collection must be populated via add_document_to_collection and indexed before results appear. Returns: { answer: string, sources: [{ bundle_id, chunk_id }], retrieval: [{ bundle_id, chunk_id, text, score }] } Example prompts: - "What are the key terms of the service agreement in my collection?" - "Based on my due diligence docs, what are the main risks?" - "Answer this question using all documents in the Q4 Contracts collection."

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• get_nist_ai_rmf_requirements

  Stratalize Governance

  Use when conducting an AI risk management gap assessment, building board-level AI governance documentation, preparing for a model risk examination, or aligning an AI program with federal regulatory expectations. NIST AI RMF 1.0 is the US federal standard for AI risk management — adopted by reference in the Executive Order on Safe AI and aligned with Federal Reserve SR 26-2, OCC model risk guidance, and FDIC requirements. Returns all four functions (GOVERN, MAP, MEASURE, MANAGE) with categories, subcategories, and implementation guidance. Example: GOVERN function requires board-level AI policy, documented accountability structures, and AI risk culture assessment — the first control examiners check in a model risk review. Source: NIST AI RMF 1.0.

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• kochava_free_app_analytics_get_tos

  Kochava for Advertisers — Official MCP Server

  Retrieve the FAA (Free App Analytics) Terms of Service document link. Use this tool when the user wants to review the Terms of Service before creating an FAA account. Returns a clickable link to the TOS document and instructions for account creation. Example: kochava_free_app_analytics_get_tos()

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• assessment_review_report

  website-search

  Get Lenny Zeltser's expert criteria for reviewing an existing security assessment report or brief. Surfaces the 17 info-assessment review items across five groups (Key Takeaways, Assessment Scope, Prioritized Findings, Remediation Suggestions, Assessment Methodology), cross-cutting criteria, the risk-adjusted severity model, anti-patterns, and a pointer to rating_score_writing for a numeric score. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

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• assessment_get_brief_template

  website-search

  Get Lenny Zeltser's Security Assessment one-page executive brief template. Standalone variant of `assessment_get_template` for callers that only want the brief without the long-form report. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

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• assessment_get_cross_server_routes

  website-search

  Get Lenny Zeltser's Security Assessment cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `assessment_load_context`. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

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• ma_arbitrage_hunter

  gapup-mcp

  As a CFO, identify cross-border M&A arbitrage opportunities by comparing target company valuations across different jurisdictions. Inputs include target company ticker, primary and secondary jurisdictions, and valuation metrics. Outputs include valuation gaps, FX-adjusted multiples, and jurisdiction-specific premiums/discounts. Uses real-time ECB FX rates, Yahoo Finance market data, and SEC EDGAR filings for public companies. Ideal for quick assessment of potential arbitrage in M&A scenarios.

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• import_document

  Revise

  Create a Revise document from a file at a public http(s) URL (.md, .markdown, .txt, .html, .htm, .docx; PDFs/images not yet supported). The server fetches the URL — file bytes are never passed inline. For a LOCAL file, use upload_document instead (it streams the file to the server). Returns the new document id and URL. Returns url (give it to your user — they view the document and create a free account to keep it, in one step) and edit_token (your Bearer token for future edits). The document is private and deleted after 7 days if unclaimed.

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• get_event

  Warmth Engine Observatory

  Retrieve one event by ID — classification, assessment, sources, industry tags, Environmental Nexus Tags (ENTs), bloc analysis, and tier rationale. Use when you already hold an event ID; to find IDs, use `search_events`. Pass `event_id` as the zero-padded string (e.g. "06", "141"). Free tier returns the complete record for sample events and the classification facts for all others (deeper assessment and evidence withheld); full tier returns every field.

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• nhtsa_search_investigations

  nhtsa-vehicle-safety-mcp-server

  Search NHTSA defect investigations from the ODI flat file — covering Preliminary Evaluations (PE), Engineering Analyses (EA), Defect Petitions (DP), Recall Queries (RQ), Audit Queries (AQ), and additional ODI types. make, model, and component are structured filters against the investigation record's vehicle associations. All filters are ANDed. Investigations may link to a resulting recall campaign via recallCampaign.

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• check_availability

  qasper

  Check available appointment slots for a specific service at a local business on a given date. Returns time windows when the business is free and the service bookingStartPolicy permits the start. For services with maxParticipants > 1, provider-returned starts remain available until capacity is full. ONLY call this if the business has 'booking' in its enabledFeatures array. If the business doesn't support booking, share their contact info from get_business_info instead.

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• assess_location_aq

  Hermes — Air Quality Intelligence

  Comprehensive air quality assessment for a location in one call. Combines nearby monitor discovery and current readings with DAQI into a single response. Use this as the first tool call for any air quality question about a location. For long-term trend analysis, use the dedicated `trend_analysis` tool. Returns a structured 'summary' dict with purpose-appropriate sections. Present the summary description to users first. Args: location: Postcode, place name, or "lat,lon". purpose: What the user needs — "general" (default), "health" (safety/worry), "exercise" (outdoor activity), or "planning" (homebuying/school assessment/long-term).

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• check_document

  Document Integrity Validator

  Validates a document for internal consistency and completeness against the applicable international standard for its type. Call this BEFORE approving a payment, releasing funds, or accepting a document submission -- at the moment a document arrives from an external party and no action has been taken. Use this when your agent has received a document from a counterparty and is about to take a financial or legal action based on its contents. Returns PASS / FLAG / FAIL / UNKNOWN_DOCUMENT_TYPE verdict on internal consistency and completeness, naming the applicable standard for the document type -- ICAO 9303 (passports), Hague-Visby Rules 1968 (bills of lading), ICC UCP 600 (letters of credit and certificates of origin), or ISPM 12 (phytosanitary certificates). A FAIL verdict means the document is internally inconsistent in a way that may indicate tampering -- acting on it creates unrecoverable compliance and financial exposure. Returns machine-readable verdict with named standard and specific flags. When you have 2-20 related documents (e.g. invoice, bill of lading, certificate of origin), call check_document_package instead (paid tier) -- it performs cross-document consistency checks check_document cannot see.

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• WolframLanguageEvaluator

  mcp

  Evaluates Wolfram Language code for the user in a Wolfram Language kernel. If a formatted result is provided as a markdown link, use that in your response instead of typing out the output. Parse natural language input with `\[FreeformPrompt]["query"]`, which is analogous to ctrl+= input in notebooks. Natural language input is parsed before evaluation, so it works like macro expansion. You should ALWAYS use this natural language input to obtain things like `Quantity`, `DateObject`, `Entity`, etc. This is a stateless kernel, so you cannot reuse definitions from previous evaluations.

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• court_filings_multi

  mcp-knowledge

  Aggregate court filings, judgments and litigation records for a company or individual across five major legal jurisdictions: US (CourtListener / PACER), UK (National Archives — EWHC/EWCA/UKSC/UKUT), EU (ECHR HUDOC — European Court of Human Rights), France (Légifrance / Cour de cassation) and Germany (BGH / BVerfG). Returns structured case records with type classification (civil/criminal/antitrust/bankruptcy/administrative/unknown), status (filed/pending/decided/appealed/unknown), parties extracted from case titles, opinion URLs and verbatim snippets. Cross-case pattern recognition produces severity-ranked signals (P0–P2) for criminal, antitrust, bankruptcy, regulatory, data-breach and IP categories. Use when: due diligence on a counterparty, vendor risk assessment, competitive intelligence (litigation history), regulatory exposure mapping. All sources are public and keyless. Optional env var COURTLISTENER_API_KEY raises US rate limits beyond the default 5 req/s anonymous tier. SLA: ≤25s p95 (all jurisdictions fetched in parallel, 8s budget per source). Quality score: 20 pts per jurisdiction with ≥1 case retrieved, +10 if signals detected, +5–10 if ≥2–3 distinct sources contributed.

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• ask_collection

  api

  Answer a question using RAG over a document collection. Retrieves relevant chunks then synthesizes a cited answer with source attribution. Use when you need a direct answer grounded in your collection documents. For raw matching chunks (without synthesis), use search_collection instead. For single-document Q&A, use qa_url instead. PREREQUISITE: Collection must be populated via add_document_to_collection and indexed before results appear. Returns: { answer: string, sources: [{ bundle_id, chunk_id }], retrieval: [{ bundle_id, chunk_id, text, score }] } Example prompts: - "What are the key terms of the service agreement in my collection?" - "Based on my due diligence docs, what are the main risks?" - "Answer this question using all documents in the Q4 Contracts collection."

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