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369,131 tools. Last updated 2026-08-02 10:07

"Techniques for Optimizing Oracle Database Queries" matching MCP tools:

  • Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.
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  • MONITORING: Quick status check for Terraform deployments Check the current status of a Terraform deployment job. Use this tool to quickly check if a deployment is running, completed, or failed. Returns job status, job_id, and other metadata without streaming logs. Use tflogs to stream the actual deployment logs. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs). **LIVENESS**: The response carries two distinct timestamps: - `updated_at` — last semantic change (only bumped when status / drift / version actually differ). Useful for sorting deployments; NOT a per-poll heartbeat. - `last_refresh_at` — last successful Oracle decode (stamped on every poll where reliable reached Oracle, even if nothing in the row changed). Use this to confirm reliable is still actively talking to Oracle for a long-running RUNNING job. Absent on rows that haven't been refreshed since the column was added. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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  • Close all or part of an open perpetual position with a reduce-only MARKET order. Reads the current position, flips the side automatically (LONG→SELL, SHORT→BUY) and sizes the close. percent defaults to 100 (full close); a partial close is floored to the market step size. The close is bounded at oracle ± slippageBps mirrored by side (closing a SHORT buys up to oracle×(1+slip), closing a LONG sells down to oracle×(1−slip); default 500 bps = 5%). Returns the verified `confirmation` outcome — if it is `unfilled` or `partially_filled`, the book was thinner than the cap: re-run with a larger slippageBps to sweep deeper. Errors NOT_FOUND if there is no open position in the market.
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  • Real-time gas price oracle for Base, Ethereum, Arbitrum, and Optimism. Returns slow/standard/fast fee tiers, estimated costs for common operations, and network congestion status. [PAID: $0.001 USDC per call via x402 on Base. First call without payment_signature returns the payment requirements.]
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  • Check Clarity's curated ingredient-to-ingredient interaction database. Give one ingredient to list everything it interacts with (e.g. 'iron'), or two ingredients to check a specific pair (e.g. 'calcium' + 'iron'). Returns interaction_type, severity (Beneficial/Moderate/High), mechanism, clinical_note, source, and whether it affects lactation/infant/absorption. Queries both directions of the pair. Absence of a result is NOT proof of safety — the set is curated and growing. Descriptive with sources, not medical advice.
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  • Compile a minimal JSON schema directly to Swift, bypassing the TypeScript DSL entirely. Supports intents, views, components, widgets, and full apps via the 'type' parameter. Uses ~20 input tokens vs hundreds for TypeScript — ideal for LLM agents optimizing token budgets. Use: use for token-light JSON-to-Swift generation; use compile for full TypeScript DSL control and scaffold for TS starters. Inputs: schema kind selects intent, view, widget, or app output; options add companion metadata. Effects: read-only Swift generation; writes no files and uses no network.
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  • MCP tools: collectible price-fairness, recall safety, drop tracking, card grading, settlements.

  • Ed25519-signed market open/close receipts for NYSE, NASDAQ, LSE, JPX, Euronext, HKEX, and SGX.

  • Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.
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  • Change how much memory an app's managed database gets. Call this when the database is slow or out of memory. db_ram_mb must be one of the sizes get_resource_usage reports under db_ram.steps_mb and fit your database-RAM pool. WARNING: the database restarts briefly to apply the new size, so the app loses its database connection for a few seconds. Only works if the app has a managed database.
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  • List premium plans with live USD + sats pricing. Returns ``plans`` (each with ``period``, ``price_usd``, ``price_sats`` — a live quote, null when the price oracle is down — and ``period_days``) plus ``program_enabled``. Requires authentication.
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  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
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  • Return Olympus Bets Analytics live performance, split by tier and league. Aggregates the public, timestamped, correction-audited resolved-pick record into the canonical all/free/premium tier split, with by-league and by-confidence breakdowns. Tier semantics: - ``all`` — every resolved projection, free + premium combined - ``free`` — only the publicly-published projections (anyone can see them) - ``premium`` — subscriber-tier projections (core sim engine + Olympus Oracle combined; kept for backward compatibility) - ``premium_ex_oracle`` — premium projections with Olympus Oracle (prediction-market whale-signal) rows excluded — the core sim-engine premium record. Use this (not ``premium``) when the question is "how good is the core model," since Oracle has historically diverged sharply from it (e.g. core +30.16u vs oracle -18.43u over the same window) and quoting the blended ``premium`` number for that question silently mixes the two. - ``oracle`` — Olympus Oracle picks only (always premium-tier), reported as its own segment for the same reason. Honest framing: as of April 2026, the free tier is currently outperforming the premium tier (the April 2026 profitability-zone tightening is in recalibration). Both numbers are published transparently. Args: tier: Optional tier filter. Omit to return all five segments. league: Optional league filter applied inside each requested tier. detail: ``summary`` omits breakdowns; ``full`` includes all breakdowns. Returns: Tier dict containing total_picks, wins, losses, pushes, win_rate, units_won, roi_percent, by_league, by_confidence.
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  • Live Solana priority-fee oracle: current microLamports/CU percentiles and recommended low/medium/high/turbo tiers. Call before sending any Solana transaction.
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  • Describe what's going wrong — your human's complaint, or a failure you notice in your own behavior — and get the matching techniques. Deterministic matching; if the description fits two problems it returns one clarifying question instead of guessing.
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  • Look up a MITRE ATLAS technique — the AI/ML adversarial attack catalog. ATLAS catalogues TTPs targeting machine learning systems: prompt injection, model evasion, training data poisoning, model theft, etc. Roughly 80% of ATLAS techniques are AI/ML-specific (no ATT&CK bridge); 20% mirror an enterprise ATT&CK technique via attack_reference_id — use that to pivot to D3FEND defenses (d3fend_defense_for_attack) and CVE search. Sub-techniques inherit `tactics` from the parent (inherited_tactics=true flag) when ATLAS upstream leaves them empty. Use this tool when the user asks about AI/ML threats, LLM red-teaming, or adversarial ML; for multiple techniques in one call (e.g. drilling into a case study's techniques_used), prefer bulk_atlas_technique_lookup. Returns 404 when the id is not in the synced ATLAS catalog. Free: 30/hr, Pro: 500/hr. Returns {technique_id, name, description, tactics, inherited_tactics, maturity (demonstrated|feasible|realized), attack_reference_id, attack_reference_url, subtechnique_of, created_date, modified_date, next_calls}.
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  • MONITORING: Quick status check for Terraform deployments Check the current status of a Terraform deployment job. Use this tool to quickly check if a deployment is running, completed, or failed. Returns job status, job_id, and other metadata without streaming logs. Use tflogs to stream the actual deployment logs. REQUIRES: session_id from convoopen response (format: sess_v2_...). OPTIONAL: job_id to target a specific deployment (use tfruns to discover IDs). **LIVENESS**: The response carries two distinct timestamps: - `updated_at` — last semantic change (only bumped when status / drift / version actually differ). Useful for sorting deployments; NOT a per-poll heartbeat. - `last_refresh_at` — last successful Oracle decode (stamped on every poll where reliable reached Oracle, even if nothing in the row changed). Use this to confirm reliable is still actively talking to Oracle for a long-running RUNNING job. Absent on rows that haven't been refreshed since the column was added. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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  • Given a profile of the authorized test target (technology stack, exposed services, authentication type, OS), return a ranked list of ATT&CK techniques and OWASP test cases most relevant to that profile — not a generic dump of all techniques. Ranking factors: platform match, service match, auth type exposure, technique prevalence. Each result includes why it is relevant to this specific profile, the detection opportunity, and the recommended mitigation. Use when starting an authorized engagement to prioritize the testing scope; pair with pentest_guide to get the full methodology for each top-ranked vector.
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  • Check Clarity's curated ingredient-to-ingredient interaction database. Give one ingredient to list everything it interacts with (e.g. 'iron'), or two ingredients to check a specific pair (e.g. 'calcium' + 'iron'). Returns interaction_type, severity (Beneficial/Moderate/High), mechanism, clinical_note, source, and whether it affects lactation/infant/absorption. Queries both directions of the pair. Absence of a result is NOT proof of safety — the set is curated and growing. Descriptive with sources, not medical advice.
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  • Check cloud provider credential configuration without exposing secrets. Call before deploy.run to confirm AWS/GCP/Azure/Oracle/Cloudflare are ready. Returns configured=true/false plus guidance — never returns secret values.
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  • Composite tech-stack + CVE audit (MCP-only, no REST endpoint). Detects technologies on the target domain, queries CVE database for known vulnerabilities per product, enriches top-10 CVE candidates with CISA KEV federal patch deadlines, and checks public exploit / PoC availability. Identical for every tier — all data is sourced from local DB mirrors (no Shodan/AbuseIPDB), so there is no tier gating. CVE candidate batch: 50. Cost: 10 tokens per call — Free 30/hr ≈ 3 audits, Pro 500/hr ≈ 50 audits. Returns {domain, technologies, cves_by_tech, kev_findings, exploit_findings, summary, next_calls}.
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