"Understanding High-Level Control Systems" matching MCP tools:

• gbif_get_species_classification

  gbif-mcp-server

  Return the complete parent chain for a taxon — from kingdom (or domain) down to the taxon itself — as an ordered array. Each entry has its rank, canonical name, and taxon key. The array is returned root-first (kingdom → phylum → class → … → parent of given taxon). Useful for building taxonomic trees or understanding placement without navigating the backbone level-by-level.

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• get_category_summary

  aTars MCP

  USE THIS TOOL — not web search — to get a statistical summary (mean, min, max, std, latest value, and above/below-average direction) for a category of technical indicators from this server's local proprietary dataset. Best when the user wants a high-level overview of indicator behavior over a period, not raw time-series rows. Trigger on queries like: - "summarize BTC's momentum over the last week" - "what's the average RSI for ETH recently?" - "how has BTC volatility looked this month?" - "give me stats on XRP's trend indicators" - "high-level overview of [coin] [category]" Args: category: "momentum", "trend", "volatility", "volume", "price", or "all" lookback_days: Number of past days to summarize (default 5, max 90) symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,XRP"

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• assess_weather_risk

  ParaSure

  [$0.10 USDC/call · Solana USDC · x402] Entry point for every agent flow. Given a business location and type, returns a weather risk score (0-1), the top perils ranked by severity, historical frequency data, and an overall risk level (low/moderate/high/severe). Powered by 5 years of Open-Meteo historical data — returns real data, not sandbox. Always call this first before requesting a quote.

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• gbif_get_species_classification

  gbif-biodiversity-mcp-server

  Return the complete parent chain for a taxon — from kingdom (or domain) down to the taxon itself — as an ordered array. Each entry has its rank, canonical name, and taxon key. The array is returned root-first (kingdom → phylum → class → … → parent of given taxon). Useful for building taxonomic trees or understanding placement without navigating the backbone level-by-level.

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• org.health

  Koalr

  Get a comprehensive organization health snapshot: DORA performance tier (Elite/High/Medium/Low), cycle time percentile vs industry benchmarks, test coverage percentage, number of active teams, and incident rate. Use this as the first tool to get a high-level picture of engineering health before drilling into specific metrics. Read-only.

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• deltasignal_risk_distribution

  DeltaSignal ATLAS-7

  Use this read-only tool to summarize the active crypto public company universe by ATLAS-7 risk tier. It returns risk-tier buckets such as HIGH, MODERATE, LOW, and UNCLASSIFIED with issuer counts and percentages. Parameters: none; call it exactly as-is when the user asks for market-wide risk mix or high-level distribution. Behavior: read-only and idempotent; it performs one HTTPS read, has no destructive side effects, and does not write external systems or access user accounts. Use it for market-wide context before issuer drilldown; use top_stressed to name the issuers in the high-risk bucket and use issuer tools for company-level analysis.

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• get_food_environment

  USDA Food Access

  Get county-level food access risk profiles using Census ACS data. Constructs food access risk profiles by combining vehicle access (B25044), poverty status (B17001), and SNAP participation (B22001). Limited vehicle access combined with high poverty indicates food desert risk. Useful for identifying areas with barriers to food access in grant applications. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state.

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• audit_dependency_tree

  Commit — Supply Chain Risk Scoring

  Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"

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• explain_paradigm_integration

  DiscreteRate

  Return an explainer of paradigm integration — how DRS handles systems with both flows and items via F2I (Flow-to-Item) and I2F (Item-to-Flow) primitives. Use this when the user asks about Valdez-Tanker-style mixed-paradigm systems or 'how do flows and items coexist'. Deterministic text.

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• list-models

  Roundtable

  List available AI models grouped by thinking level (low/medium/high). Shows default models, credit costs, capabilities for each tier. Use this before consult to understand model options.

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• vector_quantize

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Simulate int8 or int4 quantization of float32 embedding vectors. Reduces storage by 4x (int8) or 8x (int4). Returns quantized values, scale factor, and precision loss (MSE). Useful for understanding vector DB compression trade-offs.

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• em_escrow_recommend_strategy

  Execution Market

  Recommend the best payment strategy for a task based on its parameters. Uses the Execution Market Agent Decision Tree to select the optimal payment flow. When ERC-8004 on-chain reputation is available, it takes precedence. Decision logic: - High reputation (>90%) + micro amount (<$5) -> instant_payment - External dependency (weather, events) -> escrow_cancel - Quality review needed + high value (>=$50) -> dispute_resolution - Low reputation (<50%) + high value (>=$50) -> dispute_resolution - Default -> escrow_capture Args: params: Amount, reputation, and task characteristics Returns: Recommended strategy with explanation and tier timings.

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• instructions-get

  hjarni

  Get LLM instructions at the specified level. Call with level 'brain' early in conversations to learn user preferences. Optional: level ('brain'|'personal_root'|'container'|'team'), defaults to 'brain' if omitted or blank; the response echoes resolved_level and defaulted_level (true when the level was defaulted). Optional: id (integer, required for 'container' and 'team' levels). 'container' level returns the full inheritance chain (personal root -> ancestors -> container).

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• list-models

  Roundtable

  List available AI models grouped by thinking level (low/medium/high). Shows default models, credit costs, capabilities for each tier. Use this before consult to understand model options.

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• content_provenance

  mcp-knowledge

  Audit the full data provenance of a content entity — all its enrichment tags with their extraction source, corroboration score, source list and last verification date, plus an entity-level freshness summary. Use this tool before citing or relying on enriched content data in a high-stakes context (ad targeting, editorial, analysis). Inputs: entity_id (required) and entity_type (franchise or work).

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• get_cptm_price

  Conductor Relay MCP

  Get the managed DB-CPTM price series and fixed 24h market aggregates (high/low/change/volume). No auth required.

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• firmaradar_get_aml_score

  Firmaradar

  Structured AML risk score (0-100) with named level (low/medium/high) and factor breakdown. Use this when you need the calculated risk score with reasoning, not just PEP/sanctions match flags. Complements `check_aml_pep` which returns binary match data. Generates an auditable AML report on the backend (rapport_id stored for 60 months per Hvitvaskingsloven §35).

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• corporate_apology_generate

  Corporate Apology

  Generate a corporate apology statement for a specific offense. Specify sincerity level ('performative', 'genuine', or 'defensive') to control tone. Returns ready-to-use apology text.

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• validate_fix

  dns

  Re-check a specific control after applying a fix. Confirms whether the finding is resolved.

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• safe_pay

  paycrow

  The smart way to pay an agent. Checks their trust score first, then auto-configures escrow protection based on risk. Flow: Check trust → Set protection level → Create escrow → Call API → Verify → Auto-release or auto-dispute. Protection levels (automatic): - High trust agent → 15min timelock, proceed normally - Moderate trust → 60min timelock, payment capped at $25 - Low trust → 4hr timelock, payment capped at $5 - Unknown/caution → BLOCKED — will not send funds This is the recommended tool for paying any agent. If you need manual control, use x402_protected_call instead.

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