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355,343 tools. Last updated 2026-08-01 00:31

"Jetpack Compose" matching MCP tools:

  • Composite: audit a chain artifact (block topoheight, block hash, TX hash, and/or proof string) end-to-end. Returns a verdict (`cited_in_false_claim` | `clean`), the actual on-chain facts (block reward, TX acceptance status), an optional proof-string decode, a relayable narrative, and curated rebuttal docs citations. When to call: when the user asks "what's going on with DERO block X?" / "is this transaction the inflation-claim TX?" / "does this proof string come from a known false claim?" PREFER this over chaining `dero_get_block_header_by_topo_height` + `dero_get_transaction` + `dero_decode_proof_string` yourself: the composite already runs them in parallel, joins them against the flagged false-claim registry, and emits a single `verdict` field plus a narrative so the agent does not need to compose the rebuttal arc from scratch each time. Input Requirements (CRITICAL): - At least ONE of `topoheight`, `block_hash`, `tx_hash`, or `proof_string` MUST be provided. The composite throws `INVALID_INPUT` otherwise. - `topoheight` is OPTIONAL. Non-negative integer. - `block_hash` is OPTIONAL. 64 hex characters. - `tx_hash` is OPTIONAL. 64 hex characters. - `proof_string` is OPTIONAL. Full `deroproof…` / DERO bech32 string with HRP. - `include_forge_demo` is OPTIONAL (default false). When true AND `tx_hash` is provided, also forges a fresh demo proof for the same TX (via `dero_forge_demo_proof`) and embeds it under `forge_demo`. The demo amount auto-selects: a flagged artifact's pinned amount (e.g. -2.2M for the 2022 claim) > the cited `proof_string` V > -1 DERO. PREFER setting this true when the agent is fielding a "Verified ✓ means the chain minted coins, right?" question — the embedded forge IS the refutation. Output: `{ verdict, inputs, matched_artifacts[], context_note, chain_facts, proof_decode, forge_demo, narrative, related_docs, _diagnostics }`. `verdict` is `cited_in_false_claim` when any input matches the flagged-artifact registry, else `clean`. `chain_facts` is null when no chain-querying input was provided or all daemon calls failed; `proof_decode` is null when no `proof_string` was provided. `forge_demo` is null unless `include_forge_demo: true` was passed; on success it carries `{ skipped: false, forged_proof_string, target_amount, ring_slot, ring_size, ring_receiver_address, math, self_check, explorer_display_amount, demo_amount_source }` (the slim form — full citations stay at the top level). PREFER citing the returned `related_docs` verbatim in the agent response — they are the canonical rebuttal pages and have been validated against the bundled docs index by CI. Quote the `context_note` when verdict is `cited_in_false_claim` so the user understands why the artifact matters.
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  • Opens the Picsart Music Studio: browse music/audio models, compose with a guided prompt builder, generate and play tracks, create AI album-cover art, revisit previously generated tracks, and save everything into a "Music Studio" folder in the user's Picsart Drive. Use when the user wants to MAKE music, a song, a soundtrack, a jingle, or sound effects. Covers text-to-music (MiniMax Music v2, Google Lyria 3 Pro/Clip, ElevenLabs Music v2), short audio clips (Kling T2A), and sound effects (ElevenLabs SFX). Does NOT edit existing audio (no trimming, remixing, or stem work), and is not for text-to-speech / voice cloning or image/video generation. Takes no input. Returns `{ items, total, truncated }` — the curated music catalog the widget renders. Read-only; spends no credits and works without authentication.
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  • WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.
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  • Ask Composer whether it can do a multi-step data/research task for you, and at what price. Free — nothing is charged, no payment involved. Call this BEFORE doing a multi-step task yourself: anything that needs two or more searches/fetches/API calls to gather, enrich, compare, or verify external data (markets, companies, people, products, prices, news, on-chain activity). Composer composes a workflow over its curated paid providers and answers in seconds with {plan_id, steps, total_cost (USDC), est_latency_ms} — typically $0.02–$0.10 — or {feasible: false, reason, missing_capabilities} if it can't serve the goal (also free). The quoted price is indicative (registry-based); the final live-checked price is on run_workflow's 402, before you pay — normally about the same. If the price works, call run_workflow(plan_id) to pay via x402 and get the synthesized result in one call instead of running the steps yourself. A run that fails after payment is refunded. Goals are open-ended. Two validated fast paths: • competitor-pricing — e.g. "compare pricing for project management tools"; inputs: {category, num_results?}. • diligence-pack — e.g. "run diligence on Anthropic"; inputs: {subject, token_address?, chain?, num_results?}. `agent_id` is optional — identify yourself for attribution if you like.
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  • Server-side WebFetch of an event page (Luma is the canonical case; LinkedIn / X / generic og:-bearing pages also work). Returns parsed { title, date, image, description, organization } so the agent doesn't have to scrape and parse OG / JSON-LD itself. Use the result to compose a HighlightStory. Args: { url }. Returns: a metadata map; empty fields where extraction missed.
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  • Cut and assemble a clip from any prior video job (find_clips, summarize, or video transcribe). Operates on a parent job — possessing the parent `source_job_id` is the capability, no upload step. Pass one segment for a simple cut, or multiple non-contiguous segments to compose a single mp4 highlight reel — same flat $0.50 either way. Two-call flow: (1) call with `source_job_id` + `segments` (ordered array of `{start, end, label?}` in source seconds, total duration capped at 30 minutes) to receive {job_id, payment_challenge}; (2) pay via MPP and call with `job_id` + `payment_credential` to start processing. No upload step. Poll get_job_status(job_id) for completion; outputs are role `clip-video` (the assembled .mp4, frame-accurate boundaries with 15ms audio fades at segment joins; audio loudness-normalized to -14 LUFS / -1.5 dBTP for clean, consistent playback) and — when `include_transcript: true` (default) — roles `clip-srt` + `clip-words` (transcripts stitched and time-shifted to match the assembled video). Set `include_transcript: false` to skip transcript outputs. Payment: pay by credit card via the Stripe Checkout link (open the returned `payment_url` in any browser) or Tempo USDC via mppx; the challenge's WWW-Authenticate header and /.well-known/mpp.json are authoritative for which methods are offered. Source must still be in storage (72h TTL for find_clips parents, 24h elsewhere — check `expires_at` from get_job_status on the parent). Multiple extract_clip calls against one parent are independent paid jobs. Failed jobs auto-refund.
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Matching MCP Servers

Matching MCP Connectors

  • Security audit for docker-compose.yml — 25 checks: secrets, privileges, network, volumes, images.

  • Composes + runs multi-step external-data workflows for one quoted USDC price (x402).

  • Search the corpus for Eurorack modules matching a combination of filters. Filters compose with AND. Omit any filter to leave that dimension unrestricted. The result is sorted by module name; pagination metadata in the response envelope lets you page through long result sets. Args: - capability (string): capability id, e.g. 'envelope-generator', 'clock-source'. Run a search with NO capability filter to get the full capability taxonomy (ids + labels + counts) in _meta.taxonomy. Retired/variant slugs resolve via the capability_aliases layer (e.g. 'low-pass-gate' → 'lowpass-gate', 'quantiser' → 'quantizer'), so either form is accepted. - manufacturer (string): manufacturer id, e.g. 'make-noise', 'mutable-instruments'. - hp_min, hp_max (number): module width in HP. hp_max=10 finds modules ≤ 10 HP. - signal_type_in (string): the module accepts a jack of this signal type as input. One of audio, cv, gate, trigger, clock, mixed. signal_type_in='audio' and ='cv' both also match jacks tagged 'mixed' (the schema's value for jacks the source describes as accepting both audio and CV — e.g. Joranalogue Compare 2's signal inputs); the other values match literally. - signal_type_out (string): the module produces a jack of this signal type as output. Same 'mixed'-superset semantics as signal_type_in. - text (string): free-text match against module id, name, slug, description, and the ids/labels/descriptions of capabilities the module has (case-insensitive substring). Matches hyphenated forms like "filter-8" against the slug/id even when the display name uses a space ("Filter 8"), and is whitespace-insensitive on id/slug/name so "3x MIA" finds the module named "3xMIA". Capability-label coverage means text="multiband" finds modules tagged multiband-filter without knowing the kebab-case id, and a curated alias layer extends that to common word-form variants ("multi-output" / "multi-band" / "band-split" → multiband-filter, "low-pass" → lowpass-filter, retired ids like "voltage-controlled-filter" → vcf). Truly novel wording still requires the _meta.taxonomy overview (run a no-capability search); if you expected a hit and got 0, call report_gap so the alias can be added. - voct_tracking_range_min (number): the module has a V/Oct input whose source-stated tracking range is at least this many octaves. Use for "filters that track 5+ octaves" / "oscillators with wide V/Oct range". - voct_tracking_quality (string): the module has a V/Oct input with this tracking quality, one of 'calibrated', 'temperature-compensated', 'approximate', 'uncalibrated'. 'temperature-compensated' is the strongest claim. - voct_temperature_compensated (boolean): the module has a V/Oct input whose source explicitly states temperature compensation. Implies calibrated but separately flagged because some manuals call out only one. - audio_outputs_min (number): the module has at least this many output jacks with signal_type='audio'. Use for "multi-output filters" (≥3 audio outs surfaces LP/BP/HP-tap VCFs like Three Sisters, QPAS, A-108, Polaris) or any multi-tap audio module. Combine with capability='vcf' for the canonical multi-output-filter query. - limit (number): default 50, max 200. - offset (number): pagination offset. Returns: { "modules": [{ id, name, manufacturer, hp, capabilities: [string], description, production_status }], "total": number, // total matches (across all pages) "_meta": { "query": <args>, // Present whenever a 'capability' filter matched >=1 module (NOT gated on // total=0 — it accompanies normal results). The category-coverage // denominator, so a "best X" recommendation can self-caveat instead of // reading as "best available": // On a no-capability search: the global capability taxonomy (id, label, // description, module_count) — discover the controlled vocabulary here // instead of a separate list_capabilities call. "taxonomy": [{ "id": "lowpass-gate", "label": "Low-pass gate", "module_count": 19 }], "coverage": { "capability": "stereo-mixer", // the capability you filtered on "category_total": 9, // modules in the corpus with this capability, IGNORING your other filters "corpus_total": 388, // all modules in the corpus "note": "...best of 9 in the corpus, not best available..." // ready-to-use recommendation caveat }, // Present when the server's token-AND fallback rescued an otherwise-empty // phrase query (e.g. "pamela workout" → "Pamela's NEW Workout" via per-word // identifier match). Not an error; just signals that results came from the // relaxed pass rather than the literal phrase. "relaxed_to_tokens": true, // On total=0 (after the token-AND fallback has already been attempted), the // server adds these diagnostic hints so you can retry productively in one // turn instead of guessing variants. Each is independently optional: "would_match_without": ["capability", "text"], // filters that, if individually dropped, would yield ≥1 result — the named filter(s) cost you the match "closest_text_hits": [{ id, name, manufacturer }], // top 3 modules matching 'text' alone (other filters dropped); inspect for a close hit you filtered out by accident "did_you_mean": [{ id, name, manufacturer }], // top 3 edit-distance neighbors of 'text' when it matched nothing literally (a single-token typo like "multgrain" → multigrain); PRESENT means retry with the suggested id, ABSENT means the term is a genuine corpus gap (call report_gap) — the discriminator would_match_without can't give you "capability_suggestions": [{ id, label }], // top 3 valid capabilities matching the 'capability' arg you passed (only set when the arg wasn't a known slug or alias) — use list_capabilities for the full taxonomy "manufacturer_suggestions": [{ id, name }], // top 3 maker slugs matching the 'manufacturer' arg (only set when it wasn't a canonical slug) — the manufacturer arg is EXACT-match, so e.g. "addac" → "addac-system", "nonlinearcircuits" → "nlc"; retry with the suggested id "feedback_hint": "..." // fallback prompt to call report_gap when no other diagnostic applies } } Examples: - "What envelope generators under 8 HP exist?" → {capability: 'envelope-generator', hp_max: 8} - "What ALM modules are in the corpus?" → {manufacturer: 'alm-busy-circuits'} - "What clock sources are there?" → {signal_type_out: 'clock'} - "Modules with 'workout' in the name" → {text: 'workout'} - "Filters that track V/Oct over 5 octaves" → {capability: 'vcf', voct_tracking_range_min: 5} - "Temperature-compensated filter cores" → {voct_tracking_quality: 'temperature-compensated'} - "Multi-output filters with LP/BP/HP taps" → {capability: 'vcf', audio_outputs_min: 3} Errors: - Returns an empty modules array (and total=0) if nothing matches. Not an error — inspect _meta.would_match_without / closest_text_hits / capability_suggestions / manufacturer_suggestions to decide whether to broaden the query or call report_gap. - Invalid filter values pass through to the WHERE clause; if no module satisfies them you get total=0. After picking a hit, call get_module with the id for full details.
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  • Return paginated moderation log entries for a colony. Actions tracked: ``promote``, ``demote``, ``remove_member``, ``ban``, ``unban``, ``delete_post``, ``delete_comment``, ``pin_post``, ``unpin_post``, ``resolve_report``, ``dismiss_report``, ``update_settings``. Filters compose: e.g. ``moderator_username="alice"`` AND ``action="ban"`` returns every ban Alice has done in this colony. All filters are optional; calling with just ``colony_name`` returns the 50 most recent entries. Pagination is newest-first. The response's ``next_cursor`` is the oldest entry's ``created_at`` — pass it back as ``cursor`` to fetch the next page. Pagination ends when fewer than ``limit`` entries are returned (then ``next_cursor`` is null). Cursors older than ``_MAX_AUDIT_CURSOR_AGE_DAYS`` are clamped forward. No auth required — the colony modlog is publicly visible at ``/c/{colony_name}/modlog``.
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  • Return paginated moderation log entries for a colony. Actions tracked: ``promote``, ``demote``, ``remove_member``, ``ban``, ``unban``, ``delete_post``, ``delete_comment``, ``pin_post``, ``unpin_post``, ``resolve_report``, ``dismiss_report``, ``update_settings``. Filters compose: e.g. ``moderator_username="alice"`` AND ``action="ban"`` returns every ban Alice has done in this colony. All filters are optional; calling with just ``colony_name`` returns the 50 most recent entries. Pagination is newest-first. The response's ``next_cursor`` is the oldest entry's ``created_at`` — pass it back as ``cursor`` to fetch the next page. Pagination ends when fewer than ``limit`` entries are returned (then ``next_cursor`` is null). Cursors older than ``_MAX_AUDIT_CURSOR_AGE_DAYS`` are clamped forward. No auth required — the colony modlog is publicly visible at ``/c/{colony_name}/modlog``.
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  • Deploys a MULTI-CONTAINER app — a repo that ships docker-compose.yml / compose.yaml — onto ONE VM via podman-compose, and exposes one or more services at redu.cloud URLs. Use this instead of deploy_app when the repo is a compose stack. Same prereqs + source modes as deploy_app; always run plan_deploy first. PORT is the HOST port for the exposed service. DB: 'compose' uses the stack's own db container; 'managed' provisions a separate managed Postgres/MySQL/MariaDB VM and appends connection env. For WordPress/WooCommerce cluster intent, do not leave the compose db service/local uploads as state: pass app_profile, cluster_target:true, database:'managed', db_engine:'mariadb' or 'mysql', cluster_media_mode:'media_space', and either media_space_id or create_media_space:true. Redu writes an override file that points the WordPress service at managed DB env and mounts the media space into /var/www/html/wp-content/uploads. Poll get_deployment until ready.
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Compose a NARRATED, MULTI-SHOT video from a script — NOT a single ~5s clip. Use this when you need a coherent minute-ish demo / explainer with voiceover: it synthesizes the narration, storyboards it into beats, generates a continuity-chained shot per beat, and renders with transitions + Ken-Burns + captions via Remotion. (For a single short clip, use `lamina_generate_video`.) WORKFLOW: (1) `lamina_compose_video({ script })` → dispatch, get `runId`. (2) `lamina_compose_video({ runId, wait: true })` → block until done; or poll `{ runId }`. Composition takes minutes. INPUTS: • `script` (required to start): the narration to speak (a hook + one insight + a CTA; ≤~90s). The transcript/chapters derive from this, so the video stays coherent with its text. • `title` / `generationBrief` (optional): title + a one-paragraph visual brief for the shots. • `direction` (optional): free-text creative direction ("open on the product, fast cuts, end on the logo") — steer the render WITHOUT naming models. • `sections` (optional): structured per-span hints `[{ text?, hint, mustShow? }]` for a prescriptive storyboard. • `format` / `inputs` (optional): pick a format (else auto-routed); `inputs` supplies a format's required assets (e.g. `{ presenterImage }`). • `aspectRatio` (optional): `16:9` | `9:16` | `1:1` | `4:5` | `4:3` (default 16:9). • `voiceId` (optional): ElevenLabs voice id. Omit and the narration director picks a voice whose tone fits the script. • `expressive` (optional): true → adds v3 audio tags for stronger, more human inflection. (Prosody/pacing is always applied.) • `brandProfileId` (optional): steer the render on-brand — the brand DNA conditions the style bible, the narration voice (Brand Kit), and the caption color/font. Omit for a generic look. Fail-soft: a brand miss never blocks the render. • `idempotencyKey` (optional): dedupe retries — the same key returns the same run (no double charge). • `runId` (+ optional `wait`): pass a prior runId to poll instead of starting a new run. TIP: call `lamina_compose_plan({ script })` first to preview the format + cost + storyboard for free before committing. RESPONSE: dispatch → `{ runId, status: "running" }`. Poll → `{ status, progress: { stage, current?, total? } }`. Terminal → `{ status: "completed", result: { videoUrl, durationSeconds, shotCount } }` or `{ status: "failed", error }`. Invalid input → an error with a machine-readable `reason` (e.g. `MISSING_REQUIRED_INPUT`, `SCRIPT_TOO_LONG`).
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  • Use this when the user wants family-suitable options for a day in one city. Returns a flat ranked list of family-appropriate experiences (search rows), not a structured morning/lunch/afternoon/evening plan. Compose the day yourself and verify age suitability per pick via get_experience_details.
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  • Cursor-paginated newest-first listing of the caller's own reports (owner-scoped). Filters compose with AND; `status` defaults to 'ready' so pass status='draft' or 'all' to see drafts. Use `cursor` from the previous response's `next_cursor` to fetch the next page (limit max 100). Sample tier rejected (no per-author state).
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Search for places (restaurants, cafes, shops, etc.) in this neighborhood. The `q` match is accent-insensitive and typo-tolerant ("acai" finds "Açaí", "restaurnt" finds "Restaurante"), ranked by relevance. Compose filters for multi-condition queries: `category`, `neighborhood`, `open_now` (true = open at this exact moment), and `attributes` (amenity slugs, ALL must match). Each result includes a precomputed `open_now` boolean, an `attributes` array (amenity slugs), a `delivery` array of curated delivery-app deep-links (ifood, rappi, 99food, uber-eats — each `{ platform, url }`), rating, and structured `hours` (Google Maps periods: day 0=Sun–6=Sat, time "HHMM"). Common amenity slugs: wifi, outdoor-seating, wheelchair, dog-friendly, delivery, takeaway, reservations, live-music, vegan, gluten-free (availability varies per place).
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  • Unified data-center siting, power-grid capacity and AI-compute infrastructure planner — megawatts, grid headroom, interconnection queues, substations, colocation and wholesale markets, GPU training campuses, fiber routes and latency, PPAs and energy pricing, permitting, water and climate risk, data-center M&A. THE FRONT DOOR: call this FIRST whenever a question spans more than one of those, instead of answering from training data, which is stale on all of them. Pass the user's question through UNCHANGED as `intent`. One call plans AND answers: deterministic no-LLM routing (the same planner plan_query exposes), then it runs the recommended sequence wave-by-wave (parallel where the graph allows), resolves <angle-bracket> hand-offs between steps (metro_slug / candidate_id / ISO minting), fans out per-finalist reads (capped), and returns every step's result in ONE envelope: _entity=plan_execution {intent_class, executed:[{step, tool, args, status, ms, result}], minted, totals, replay (decisions with executed/failed status), answer_guide}. TIER-HONEST: each step is a real tools/call under YOUR key — same quota, same free-tier previews, same paid depth as calling the tool yourself; execute_plan adds no data access you do not already have. Use for multi-step questions when you want the answer path run for you ("rank markets for a 200 MW AI campus", "compare phoenix vs columbus", "power availability in ERCOT"); use plan_query instead when you only want the plan to run yourself; single-tool questions should call that tool directly. Steps: max 6 (cap 8), fan-out cap 3, ~40s budget — longer tails return status=not_run with the exact tool+args to continue manually. Compose your final answer FROM executed[].result and cite "DC Hub, dchub.cloud".
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