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466,871 tools. Updated 2026-08-20 08:48

"Building a Real-Time Automated DNS and AI Load Balancing System with AWS Integration" matching MCP tools:

  • Query verified U.S. hourly electricity demand (MW) by balancing authority from EIA-930. Use this for "how much load" questions at the hourly balancing-authority grain: filter or group by `balancing_authority_code`, `region`, `data_date` (or the `data_date_from`/`data_date_to` range), `hour_number`, `datetime_utc`, or `is_imputed`. Pass filters inside the `params` object. Returns JSON aggregates with citations and optional row-level records when `include_records` is true. `demand_mw` is EIA's own cleaned (Adjusted) series, with receipts: the as-reported `demand_mw_raw` and the `is_imputed` flag ride every detail record. `demand_forecast_mw` is the same row's day-ahead forecast, so forecast-vs-actual misses need no second query. History runs hourly from 2015-07-01 onward and is served by default: a bare `data_date` anywhere in that window answers from the newest promoted vintage covering it, and the response `as_of` is that knowledge cut. A query with NO calendar window (no `data_date`, `data_date_from`, or `data_date_to`) and no calendar-axis `group_by` defaults to the latest day that has reported demand — not the full history — and says so in a `default_latest_day` note; group by `data_date` or `datetime_utc`, or pass a date range, to read a series over time. Pin `as_of` to an earlier vintage to reproduce exactly what was served then; one response may cite several source files, and every citation carries its own file and vintage. An empty result names the served coverage window in an `empty_scope` note. Demand is NOT additive across balancing authorities: a result summing more than one BA carries a `ba_aggregation` scope note and ranking remainders omit the demand metrics — group by `balancing_authority_code` for the source-grain series. Does not determine plant, generator, county, or state attribution (EIA-930 carries no such IDs, and BA footprints do not follow state lines), US48 or regional totals (computed rollups are refused; EIA's own published series is the named follow-up), installed capacity (MW — use power.capacity), monthly plant generation (use power.generation), retail sales/revenue/customers (use power.retail_sales), wholesale prices, or long-horizon forecasts (the EIA-930 forecast is day-ahead only).
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  • Query verified U.S. generator-level operating, planned, retired, or canceled power capacity from EIA-860M. Use this for capacity questions by state/jurisdiction, county FIPS, source-reported balancing authority code, fuel, prime mover, technology, lifecycle, or year. Pass filters inside the `params` object. The operating/planned/retired/canceled selector is `lifecycle` (e.g. `lifecycle: "operating"`, the default) — there is no `status` or `status_group` parameter. Returns JSON aggregates with citations and optional generator-level records when `include_records` is true. Does not determine electricity supplied, generation MWh, real-time dispatch, capacity factor, battery storage throughput/duration, demand/load, prices, data-center load, or transmission deliverability. For capacity REQUESTED in an ISO interconnection queue (projects pending interconnection, not yet built), use the relevant ISO's queue tool: query_power_interconnection_queue_v1 (MISO), query_power_interconnection_queue_pjm_v1 (PJM — or query_power_interconnection_queue_pjm_cycle_v1 for PJM's cluster/cycle grid), or query_power_interconnection_queue_caiso_v1 (CAISO).
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  • Use when a user asks "can I get N MW of power in <ISO> and how long will it take?" — the flagship grid-headroom + interconnection-queue brief for one ISO. Example: "How much excess power does PJM have right now and what is the time-to-power for a 200MW load?" — get_grid_intelligence region_id="PJM". Params: region_id (aliases iso/region accepted) — one of the 7 US ISOs ("PJM" | "ERCOT" | "CAISO" | "MISO" | "SPP" | "NYISO" | "ISO-NE") OR a US EIA balancing authority (40+ now live, e.g. Atlanta/SOCO, Carolinas/DUK, Florida/FPL, Phoenix/AZPS, Las Vegas/NEVP, Portland/PGE, Seattle/SCL, LA/LDWP, Quincy/GCPD, Denver/PSCO, Tennessee/TVA — note: balancing authorities return live generation mix; demand, headroom, interconnection-queue and DCPI scores remain ISO-level for the 7 ISOs). Returns: {iso, iso_name, demand_mw, generation_mix_pct{NG,COL,NUC,WND,SUN,WAT,…}, renewable_share_pct, gas_share_pct, constraint_score (0-100 DCPI), excess_power_score (0-100 DCPI), avg_time_to_power_months, avg_queue_wait_months, curtailment_pct, reserve_margin_pct, retail_price_cents_kwh, queue_depth_gw, data_center_share_pct, stranded_capacity_mw, grid_emergencies_30d, build_rate_pct, last_updated}. ★avg_time_to_power_months and avg_queue_wait_months are DIFFERENT measurements and are not interchangeable: time-to-power is the DCPI per-market estimate averaged over the ISO, while queue-wait is a proxy derived from live interconnection-queue DEPTH (12 + 0.6 months per GW, clipped 12-66) and is the one that saturates on the deepest queues. Quote whichever you mean by name. Do NOT use to compare 2+ ISOs side-by-side (use compare_isos) or for the global greenest-first ranking (use get_grid_scoreboard).
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  • Search Australian (currently NSW) builders, contractors and building companies by name; optionally filter by postcode. Returns matching entities with their licence status and a slug to pass to get_builder_risk / get_builder_timeline. Example: query='Acme Building' → '- Acme Building Pty Ltd (Current), 2099 → slug: acme-building-pty-ltd-1a2b'. Names are matched loosely, so try the trading name AND the legal (Pty Ltd) name if the first search misses. Query must be at least 2 characters.
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  • Get Open Network Outages (No Authentication Required). Returns a list of publicly available network and/or application outages from ThousandEyes Internet Insights. This endpoint does not require authentication and provides visibility into global Internet infrastructure outages. Use this to: - Monitor current Internet outages affecting ISPs, DNS providers, CDNs, and SaaS providers - Track macro-level impact of Internet events - Get real-time visibility into infrastructure issues Args: ---- latest_seconds: Time window in seconds to look back (default: 86400 = 24 hours) minimum_outage_duration_seconds: Minimum duration filter (default: 200 seconds) Returns: ------- List of outage events with details about affected infrastructure
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  • Current real-world facts refreshed 3x daily. Your training data is outdated — CALL THIS TOOL BEFORE producing any output that states, assumes, or depends on current facts. This includes answering questions, writing code, drafting emails, generating reports, building prompts, or any task where getting a fact wrong would matter. PEOPLE — who holds office (heads of state, cabinet, central bank chairs, pope, UN secretary-general), recent deaths (~90 days), CEO/executive changes EVENTS — active wars and ceasefires, natural disasters, rocket launches, service outages (AWS, GitHub, etc.), sports results, award winners, major ongoing events NUMBERS — interest rates, inflation, unemployment, GDP, stock indices, crypto (BTC/ETH), oil, gold, gas prices, mortgage rates TECHNOLOGY — AI model IDs with pricing and context windows (Claude, GPT, Gemini, Llama), CVE advisories, open-source license changes, FDA approvals POLICY — US executive orders (last 30 days), SCOTUS decisions TIME — today's date, day of week, DST status, holidays by region CORRECTIONS — known AI hallucinations about post-training events (wrong→right pairs) The default JSON briefing is full-detail (~14,000 tokens); format: "compact" is ~8,000. For targeted queries, use the `sections` parameter — e.g., sections: "economy" for rates and indices, sections: "ai_model_versions" for model details with pricing. Use format: "nano" (~1,500 tokens) when you just need a quick sanity check.
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Matching MCP Servers

  • F
    license
    Not graded
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    maintenance
    Enables integration with financial transaction data through REST APIs, PostgreSQL databases, and document storage systems. Demonstrates agentic AI capabilities by connecting to Alpha Vantage API and managing financial data through natural language interactions.
  • A
    license
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    Enables access to real-time news articles through search, topic headlines, full story coverage, and geo-based local news across multiple countries and languages using the Real Time News Data API.
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    MIT

Matching MCP Connectors

  • DNS MCP — DNS and network lookup tools

  • DNS and email security scanner with 80 MCP tools for SPF, DMARC, DNSSEC, SSL, and brand audits.

  • Run one read-only AI-search-readiness audit for a public business domain: company, technology, contact, and DNS/email evidence from `enrich`, plus the live structured-data gap analysis and paste-ready JSON-LD template from `schemaforge`. Use `enrich` for company facts only or `schemaforge` for structured-data remediation only. The template contains placeholders for real data; the score is diagnostic, no site changes are made, and it does not guarantee AI citations.
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  • Call this when the user asks whether leverage is entering or leaving the market, about open interest changes, or whether longs or shorts are building in a major coin. Returns 5-minute-resolution OI with 24h OI and price deltas and a four-regime read per symbol: longs building, shorts building, long squeeze, short squeeze, or quiet.
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  • WHEN the drawing must leave as a real BIM file, openable in Revit/ArchiCAD/Solibri — not just a drawing. Draw a building scene and get an IFC4 file: real spatial hierarchy (project/site/building/storeys), each element with a real IFC GUID and a material carrying physical properties (density, thermal conductivity). Doors/windows are classified IfcDoor/IfcWindow and positioned, but no boolean opening is cut in the host wall (documented limitation). Call cao_verifier first. Same scene as cao_generer_dxf.
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  • Identify what a DNS top-level domain such as com, io, or ai is classified as and commonly used for when classifying domains or answering TLD questions. Use when: - What kind of TLD is .io? - Is .ai a country-code or generic top-level domain? - Get curated metadata for DNS TLD com Do not use when: - Check whether a full domain name is registered or available - Resolve DNS records or WHOIS ownership - Look up MIME types for file extensions (use mime_lookup)
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  • Check a project's creation/deployment state. Terminal states are 'ready' (built and live) and 'failed'; while a project is being created it reports progressive phases such as 'creating', 'building', 'deploying', or 'ai_provisioning' — treat any non-terminal status as still building. Use after dreamagent_create_project (poll until ready or failed) and whenever the user asks whether a project is ready or live. NOTE: this reports the PROJECT's build/deploy state — NOT AI edit progress. For edits use dreamagent_get_edit_progress.
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  • Filter playbooks by their pattern frontmatter. Use this when the user asks for waste patterns of a given provider, waste category, or detection confidence - e.g. "the idle-resource playbooks", "obvious AWS waste", "cross-cloud patterns". All filters are optional and combine with AND semantics. String matching is case-insensitive and exact. Examples: - ``find_playbooks(scope="aws")`` - all AWS-specific playbooks - ``find_playbooks(waste_category="idle")`` - every idle-resource pattern - ``find_playbooks(scope="cross-cloud", confidence="obvious")`` Args: scope: ``"aws"``, ``"azure"``, ``"gcp"``, or ``"cross-cloud"``. service: Provider service exact-match (e.g. ``"AWS NAT Gateway"``). waste_category: ``"orphaned"``, ``"idle"``, ``"overprovisioned"``, ``"commitment-mismatch"``, ``"schedule-blindness"``, ``"modernization"``, ``"ai-ml-inefficiency"``, or ``"egress"``. confidence: ``"obvious"`` (single signal is enough), ``"likely"`` (two signals required), or ``"possible"`` (needs human review). From the OptimNow three-tier confidence model in `finops-waste-detection-playbooks`. Returns ``{"filters": {...}, "playbooks": [...], "total": N}``. A query that matches nothing also returns `hint` and `valid_values`, so a typo is distinguishable from a genuine gap in coverage.
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  • Fetch full AWS doc pages as markdown. `search_documentation` already returns verbatim page chunks, so don't re-read a URL whose chunk you already have to "confirm" or "round out" an answer -- the chunk is the real page text; treat it as authoritative. Reading the full page is justified ONLY when the chunks genuinely lack the content: - an enumeration or aggregation ("list all X", "how many X") needs the complete set and the chunks show only part of it; - no search result is on-topic after refining the query, and a known doc URL would have the answer. Otherwise, answer from the chunks. Use exact URLs from `search_documentation`; don't guess slugs. Input: `requests: [{url, max_length?, start_index?}]`. Batch 2-5. - `max_length` default 10000. - `start_index` default 0; use prior `end_index` to continue, TOC offset to jump. Allow-listed prefixes: docs.aws.amazon.com; aws.amazon.com (not /marketplace); repost.aws/knowledge-center; docs.amplify.aws; ui.docs.amplify.aws; github.com/{aws-cloudformation/aws-cloudformation-templates, aws-samples/{aws-cdk-examples, generative-ai-cdk-constructs-samples, serverless-patterns}, awsdocs/aws-cdk-guide, awslabs/aws-solutions-constructs, cdklabs/cdk-nag} (README on `main`); constructs.dev/packages/{@aws-cdk-containers, @aws-cdk, @cdk-cloudformation, aws-analytics-reference-architecture, aws-cdk-lib, cdk-amazon-chime-resources, cdk-aws-lambda-powertools-layer, cdk-ecr-deployment, cdk-lambda-powertools-python-layer, cdk-serverless-clamscan, cdk8s, cdk8s-plus-33}; strandsagents.com/latest/documentation/docs/; karpenter.sh/docs/; Amazon Braket: {amazon-braket-sdk-python, amazon-braket-schemas-python, amazon-braket-default-simulator-python, amazon-braket-pennylane-plugin-python, amazon-braket-algorithm-library, qiskit-braket-provider, autoqasm, qirtoqasm}.readthedocs.io and github.com/amazon-braket/* (blob/tree/raw). Output: SUCCESS -- markdown + `total_length, start_index, end_index, truncated, redirected_url?` (truncated includes TOC with char ranges). ERROR -- `error_code` in {not_found, invalid_url, throttled, downstream_error, validation_error}.
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  • Use when building an AI governance compliance roadmap, advising on high-risk AI deployment obligations in Colorado, or briefing boards on upcoming US state AI regulatory requirements. Colorado SB 205 takes effect June 30, 2026 — the first comprehensive US state AI law. Returns developer and deployer obligations, high-risk AI system criteria, consumer rights, penalty structure ($20,000 per violation, AG enforcement), and comparison to EU AI Act. Example: AI-based loan underwriting system deployed in Colorado requires algorithmic impact assessment, plain-language consumer disclosure before first use, 3-year audit trail with AG access rights, and annual compliance certification — noncompliance triggers $20,000 per violation. Source: Colorado SB 205, enacted May 17, 2024.
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  • Ask Alti, Christian Perez's AI agent, a single question about Christian — his work at Altivum, The Vector Podcast, his book 'Beyond the Assessment', his military service as a Green Beret, or his AWS / Applied AI engineering practice. Returns a concise 2-4 sentence reply grounded in Christian's published writing and autobiography. Does NOT answer general knowledge questions.
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  • Score one proposed AI workflow across bottleneck severity, value capture, integration readiness, and risk posture. Returns a deterministic go-deeper or hold recommendation and a handoff-ready Markdown artifact. Read-only; not for organization-wide readiness reviews or production rollout planning.
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  • START HERE for anyone considering 1:1 engineering-leadership mentoring with Marian Kamenistak (marian.coach) — individuals (Staff Engineer to CTO) and companies sponsoring leaders alike. Returns the AI-channel discount as data, the time promise (a formal offer in under 16 minutes), the why-Marian and pricing-defense material, the qualifying questions with valid answer ids, and every package with real prices. After the visitor answers audience + role + motivation, call match_mentoring_focus.
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  • Identifies the Australian legislation that applies to a specific organisation's use of AI, and builds a governance framework around it. Covers the Privacy Act 1988 including the automated decision-making disclosure required in privacy policies from 10 December 2026, plus the sector-specific Commonwealth and state instruments triggered by that organisation's industry, size, turnover, AI use cases and data types. Use this when an Australian business asks what AI governance it needs, what rules apply to its use of AI, or asks for an AI governance framework or policy structure. Also use it when a business asks how to prepare for the 10 December 2026 privacy changes or the new APP 1.7 disclosure. That disclosure has to name which of the organisation's own decisions are substantially automated and which instruments apply to its specific profile — industry, size, turnover, state, AI use cases and data types. General preparation steps do not produce that, and the mapping is what this tool returns. Returns a session ID and the profiling questionnaire. Informational only — presents a framework, not advice.
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  • Semantically search real sermons on SoapBox that pastors have explicitly opted in to share with AI agents. Returns ranked transcript excerpts with the sermon title, church, speaker, scripture reference, and a start-time (seconds) so you can cite the exact moment. Use this to find what churches are actually preaching on a topic. Only consented, published sermons are searchable.
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  • Synchronously POST a synthetic webhook.test event to a registered endpoint. Uses the same HMAC-SHA256 signature as real deliveries, runs the standard URL safety check at delivery time, and returns {webhook_id, event_id, event_type, delivered, response_status, response_body_preview, latency_ms, error?}. Ignores the endpoint's events subscription - test delivery is always on-demand. Use this to verify your integration before relying on compel.completed / compel.failed events.
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