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304,680 tools. Last updated 2026-07-16 06:22

"AI Tool for Screen Grabbing and Graphic Design Analysis" matching MCP tools:

  • Use this read-only screening tool to rank the most stressed crypto public companies in the active DeltaSignal slice. It returns issuer rows sorted by stress, including ticker, period, risk tier, stress values, debt-coverage status, quality flags, linkbase provenance, live-price indicators, and pagination metadata. Parameters: limit is 1-100 and should usually be 5-20 for summaries; offset is only for pagination after a previous screen. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, and never writes orders, files, accounts, or wallet state. Use it for portfolio triage, issuer watchlists, and deciding which companies deserve deeper covenant or alpha analysis; use covenant_stress with ticker for detail on one issuer.
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  • Screen ONE natural PERSON's full name against sanctions (OFAC, EU, UN) and PEP lists. IMPORTANT — this is a PERSON tool only. Do NOT pass a company name, an organisation number (orgnr), or any non-person string here. For company-level AML risk use `firmaradar_get_aml_score` (by orgnr); to screen a company's owners/officers, first resolve the people via `firmaradar_get_company_roles` / `firmaradar_get_company_ownership`, then screen each PERSON name with this tool. Compliance-critical: PII-sensitive, requires a signed DPA and a legitimate purpose per call (free-text `purpose` parameter). Audit-logged for 60 months. Rate-limited to 50 calls / 30 min per API-key. Returns structured hits with category, sources, and match-ratio (default min 0.85).
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  • Get Lenny Zeltser's IR one-page executive brief template. Standalone variant of `ir_get_template` for callers that only want the brief without the long-form report. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's CTI one-page executive brief template. Standalone variant of `cti_get_template` for callers that only want the brief without the long-form report. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Use this tool when you need to screen tokens at high frequency and full holder concentration analysis is cost-prohibitive, or when you need a sub-3s response. Input the contract address and chain. Returns deployer age, LP lock status, and SAFE/CAUTION/AVOID — so you can filter obviously-risky tokens before deciding whether to pay for a full check_token_safety call. Example input: {"contractAddress":"0x1234567890abcdef1234567890abcdef12345678","chainId":"base"} Example output shape: {"riskScore":55,"recommendation":"CAUTION","deployerAgeDays":3,"deployerFlag":"WARN","lpLocked":false,"lpFlag":"WARN","processingMs":1100}
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  • Run a Sieve IMPACT-X Quick Screen on a startup. Analyzes the company across 7 dimensions (Innovators, Market, Product, Advantage, Commerce, Traction, X-Factor) and returns an analysis ID. Takes 2-5 minutes to complete. Upserts -- if the company was previously screened, returns the existing deal (set confirm=true to re-screen). Two ways to use: - v3 (recommended): First add documents with sieve_dataroom_add, then call sieve_screen(deal_id=...) to analyze everything in the data room. - v2 (legacy): Call sieve_screen(company_name=..., website_url=...) directly. At least one of website_url or pitch_deck_text is required in this mode. Args: company_name: Name of the startup to screen (v2 flow, or to create new deal). deal_id: Screen an existing deal by ID (v3 flow -- use after sieve_dataroom_add). website_url: Company website URL (v2 flow). pitch_deck_text: Extracted pitch deck text (v2 flow). description: Brief company description (optional). confirm: Set to true to re-screen an existing deal.
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  • Search the AI Tool Directory catalog: tool details, status checks (alive/acquired/deceased + cause and date), alternatives, and side-by-side comparisons. Read-only.

  • Screen a business or person for exclusions, debarment, and sanctions (SAM.gov, OFAC).

  • Sends the user's answer to a follow-up question raised by the design agent during perspective creation, then re-runs the design step. Returns a new pending job_id; long-poll perspective_await_job for the next terminal state. Behavior: - Appends the user's reply to the design conversation and kicks off another design pass. Each call starts another pass. - ONLY valid while the perspective is in DRAFT status. Errors with "This perspective already has an outline. Use the update tool to make changes." otherwise. - Errors when the perspective is not found or you do not have access. - Returns "pending" immediately. perspective_await_job resolves to "ready" (outline generated) or "needs_input" (another follow-up — call this tool again). When to use this tool: - perspective_await_job returned status "needs_input" with a follow_up_question and you have the user's reply. - Continuing the design dialogue before any outline is generated. When NOT to use this tool: - The perspective already has an outline — use perspective_update for revisions. - Starting a new perspective — use perspective_create. - Polling a previously-enqueued job — use perspective_await_job.
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  • Use this read-only screening tool to rank the most stressed crypto public companies in the active DeltaSignal slice. It returns issuer rows sorted by stress, including ticker, period, risk tier, stress values, debt-coverage status, quality flags, linkbase provenance, live-price indicators, and pagination metadata. Parameters: limit is 1-100 and should usually be 5-20 for summaries; offset is only for pagination after a previous screen. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, and never writes orders, files, accounts, or wallet state. Use it for portfolio triage, issuer watchlists, and deciding which companies deserve deeper covenant or alpha analysis; use covenant_stress with ticker for detail on one issuer.
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  • Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Get Lenny Zeltser's Malware 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 `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Get Lenny Zeltser's Malware frameworks (primary frameworks the brief structurally derives from) plus optional sibling frames (adjacent frameworks that aren't the structural backbone). Pass `include_siblings: false` to skip sibling blocks. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • 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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  • 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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  • One-call compound tool. Submit a concept, medium, audience, and constraints — receive a complete design package: historically grounded palette, cultural narrative, commercial paint matches, WCAG accessibility check, illuminant behaviour, and a ready-made image generation prompt. Replaces chaining query_conceptual + palette_from_concept + colour_story + match_paint_system + accessibility_check + get_colour_metrics. Use when an AI agent or user needs a complete, deployable colour direction in a single call. Not for iterative refinement — use individual tools for that.
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  • The user's remaining monthly analyse and AI credits and the reset date. Call when the user asks about their usage limits, or after a credit-limit error from an analysis tool.
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  • Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.
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  • Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.
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  • Returns Makuri's regulatory posture across EU AI Act, GDPR, GDPR-K (children data), COPPA, and ISO 42001 — as design intentions and operator self-assessment, NOT certified or audited compliance. No formal audit or conformity assessment has been performed. Statuses are design_aligned_unaudited, not_started, or not_applicable; there is deliberately no 'compliant' status. Use when the user asks about regulatory compliance, AI Act classification, or data protection for children — and present results as posture, not certification. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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  • Use this read-only tool for ATLAS-7 covenant stress analysis on crypto public companies. Pass ticker for a single-issuer detail view, or omit ticker to screen the active issuer universe with risk, quality, debt-coverage, linkbase, minimum-stress, limit, and offset filters. It returns filing-backed stress, headroom, risk tier, debt coverage, quality, linkbase provenance, live-price deltas, and metadata needed for covenant-risk research. Parameters: ticker selects detail mode; without ticker, limit/offset paginate list mode, min_stress is 0-100, and risk_tier, quality_flag, debt_coverage_status, and linkbase_only narrow the screen. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, and does not change filings, portfolios, wallets, or account state. Use top_stressed for the default ranked universe, peer_ranking for relative peer context, and alpha_signals when the user asks for opportunity or edge rather than covenant stress.
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  • Get the AI Defense Matrix evaluation playbook for assessing an AI security program: per-cell prompts, gap-inventory template, and a workflow that walks each asset class first and rolls findings up to the Govern column. Supports mode='gate' for binary deployment-gate decisions (returns the deployment-gate workflow plus gate-tier prompts only) and consumerPattern for scoping to consumed-vs-built AI deployments. The AI applies these prompts against your program documentation locally, and no program details leave your client. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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