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304,944 tools. Last updated 2026-07-22 11:23

"3D modeling tutorial for creating a table tennis bat in Blender" matching MCP tools:

  • Create a B2 cloud-backed snapshot (zero local disk, async). Streams container data directly to Backblaze B2 via restic. No local disk impact — billed separately at cost+5%. Runs in background — returns immediately with status "creating". Poll list_snapshots() to check when status becomes "completed". Only available for VPS plans. Requires: API key with write scope. Args: slug: Site identifier description: Optional description (max 200 chars) Returns: {"id": "uuid", "name": "...", "status": "creating", "storage_type": "b2", "message": "B2 cloud snapshot started. Poll list_snapshots()..."} Errors: VALIDATION_ERROR: Not a VPS plan or max snapshots reached
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  • Generates a voiceover from text using Hume Octave TTS. Audio uploaded to Spaces, signed URL returned (24h TTL by default). Charged in credits up-front based on script length (use quote_voiceover for a preview). Best for demo-video narration, tutorial audio, and any one-shot batch TTS. NOT a real-time conversational voice (use Hume EVI for that, different product). Voice options: pass voiceId for a specific Hume voice clone, or omit to use the deployment's default narrator (HUME_OCTAVE_VOICE_ID env var).
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  • Returns 300mm wafer price ranges (min/avg/max USD), defect density, NRE/mask-set cost, and node maturity for: tsmc-n3, tsmc-n5, tsmc-n7, tsmc-28, samsung-3nm, samsung-5nm, intel-16. Optional `node` filter narrows to one. USE THIS for: looking up wafer cost for cost modeling, comparing foundries at the same node. DO NOT USE for: per-chip cost (use get_accelerator_costs or calculate_chip_cost); packaging-related cost (use get_packaging_costs). Returns INVALID_PARAMS if node is not in the valid set. Each record carries the source attribution string. Refreshes monthly.
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  • Return today's (or a given date's) game schedule for a league. Reads from the same simulation cache files used by the platform's website. Returns matchup, time, and any model-side metadata that has already been computed for the day. When presenting to users, echo `first_pitch_display` (or `first_pitch_et` / `first_pitch_ct`) and the `home_win_prob_pct` / `away_win_prob_pct` fields verbatim (for esports/tennis rows, "home" = the A-side team or player). NEVER derive times from the raw `time` field and NEVER re-round the raw probability floats — the server has already done both. Args: league: One of NBA, NHL, CBB, NFL, MLB, SOCCER, LOL, CS2, TENNIS, WNBA, CFB, GOLF. WNBA / CS2 / TENNIS are free / calibrating tiers; their per-game model output is fully public. NFL / CFB return their most recent slate (offseason as of mid-2026). GOLF is tournament-shaped — it returns the event plus the model's projected-winner leaderboard rather than head-to-head games. date: YYYY-MM-DD. Defaults to today (Eastern time). Returns: Team / esports / tennis leagues: ``{league, date, count, games: [...]}``. GOLF: ``{league, date, event, round, count, projected_winners: [...]}``.
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  • Enumerate every 2D/3D view ('scene') baked into the translated model, plus a shallow dump of the model object tree (first 50 top-level nodes across all 3D views), plus the list of completed derivatives (svf2, thumbnail, obj, etc.) available via APS. The canonical discovery tool for anything downstream that needs a view name or GUID. When to use: before tm_render_image (to pick a valid camera_preset), before tm_export_video (to plan a camera path across named views), to audit what was translated ('did the 3D coordination view survive translation?'), or to expose the top-level model hierarchy for UI display. Also a useful health check — if scene_count=0, the translation is incomplete or failed. When NOT to use: not for full property queries on individual objects (this tool returns names + GUIDs + child counts only — use a dedicated property-query tool for full attribute dumps), not for geometry data (use tm_export_video for OBJ export), not on a URN that has not yet started translating. APS scopes required: viewables:read data:read. Read-only across Model Derivative manifest + metadata + object-tree endpoints. Rate limits: APS default ~50 req/min. This tool fans out across every 3D view to fetch object trees — for models with many 3D views (10+) it can burn a chunk of the budget in one call. Prefer caching the result on the caller side rather than re-invoking. Errors: 401/403 = token/scope; 404 = URN not found; 422 = n/a; 429 = back off 60s (this tool makes multiple APS calls per invocation, so 429 is more likely than on single-call tools); 5xx = APS upstream. A 202 on object-tree means APS is still building the tree — the tool retries once internally. Side effects: NONE on APS (read-only). Writes a usage_log row. Idempotent.
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  • Return a table surface's column definitions so an agent knows what keys create_row/update_row will accept. Each column has `key` (the field name in row.data), `label` (human-readable), `type` (text | longtext | url | status | owner | date | number), `position`, and, for status/owner columns, the allowed `options`. Empty array on doc-only workspaces; callers should still be able to write rows (columns auto-seed on first write). Multi-surface workspaces accept `surface_slug` to scope to a specific table sheet (use `list_surfaces` to enumerate); omit to fall through to the workspace's primary table surface.
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  • Tennis Grand Slams 2026 MCP — Australian Open, Roland Garros, Wimbledon, US Open. Draws + venues.

  • ifsc-in MCP — Indian bank branch IFSC code lookup via Razorpay's open

  • Fetch dimension definitions and valid coded values for a MakStat PxWeb table. Path must end in the '.px' table id (e.g. 'Naselenie/VencaniRazvedeni/280_VitStat_Brak_voz_ml.px'). Returns dimensions with their codes and value lists — use these to build the selection body for query_table.
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  • Full NBP exchange-rate table of PLN rates for many currencies at once. Pick a table: A = major currencies (mid-rate), B = other/minor currencies (mid-rate), C = bid/ask trading rates for the major set. Rates are PLN per 1 unit of each currency (per 100 for some minor units). Defaults to the latest published table; optionally pass a single date (YYYY-MM-DD) or last_n for the N most recent tables. Weekends/Polish holidays have no data (404).
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  • Fetch dimension definitions and valid coded values for a Moldova Statbank PxWeb table. Path must end in the '.px' table id (e.g. '20 Populatia si procesele demografice/POP010/POPro/POP010100rcl.px'). Returns dimensions with codes and value lists — use these to build the selection body for query_table.
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  • Read public requirements for a PrintYourDuck manual custom 3D printing quote request. Use this before submit_quote_request to check accepted file types, material options, confirmations, restrictions, and the private-upload flow. Does not calculate instant pricing.
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  • Spot agricultural commodity price from FRED IMF primary commodity series for soybeans, wheat, corn, cotton, or coffee. Returns USD price, unit, and observation period for crop hedging, food cost modeling, and trade exposure agents. Source: FRED / IMF. $0.02 atomic. Cryptographically attested with a post-quantum signed settlement receipt. Verify at trust.stratalize.com/verify.
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  • Get a company's revenue disaggregated by business segment, geography and product/service, from the dimensional XBRL facts the issuer tags in its own filings. Annual fiscal years only, latest restated values, one table per axis the company reports; values are as-reported and never estimated. Rows within one table can OVERLAP when the issuer tags several granularities on the same axis (a parent segment alongside its components), so never sum rows to derive total revenue — use the consolidated total row each table carries. For consolidated figures use GetFinancialStatement or GetFinancialFact.
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  • Run a SQL query in the project and return the result. Prefer the `execute_sql_readonly` tool if possible. This tool can execute any query that bigquery supports including: * SQL Queries (SELECT, INSERT, UPDATE, DELETE, CREATE, etc.) * AI/ML functions like AI.FORECAST, ML.EVALUATE, ML.PREDICT * Any other query that bigquery supports. Example Queries: -- Insert data into a table. INSERT INTO `my_project.my_dataset`.my_table (name, age) VALUES ('Alice', 30); -- Create a table. CREATE TABLE `my_project.my_dataset`.my_table ( name STRING, age INT64); -- DELETE data from a table. DELETE FROM `my_project.my_dataset`.my_table WHERE name = 'Alice'; -- Create Dataset CREATE SCHEMA `my_project.my_dataset` OPTIONS (location = 'US'); -- Drop table DROP TABLE `my_project.my_dataset`.my_table; -- Drop dataset DROP SCHEMA `my_project.my_dataset`; -- Create Model CREATE OR REPLACE MODEL `my_project.my_dataset.my_model` OPTIONS ( model_type = 'LINEAR_REG' LS_INIT_LEARN_RATE=0.15, L1_REG=1, MAX_ITERATIONS=5, DATA_SPLIT_METHOD='SEQ', DATA_SPLIT_EVAL_FRACTION=0.3, DATA_SPLIT_COL='timestamp') AS SELECT col1, col2, timestamp, label FROM `my_project.my_dataset.my_table`; Queries executed using the `execute_sql` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `projectId` field.
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  • Returns reference data for a supported MLP ticker — current cash distribution per unit, distribution growth CAGR, default return-of-capital percentage, distribution coverage ratio, K-1 entity count, operating-state count, and last-verified date. Use when: User wants to look up baseline characteristics of an MLP before modeling — e.g., comparing distribution coverage across partnerships, checking how many K-1 entities a holding generates for tax-prep complexity, or seeing the operating-state count for state-tax filing-burden estimation. Don't use for: Tax computation. Use mlp_projection (long-horizon modeling), mlp_estate_planning (estate analysis), mlp_sell_vs_hold (break-even sell price), or k1_basis_compute / k1_basis_multi_year (computing basis from actual K-1 data). Note: This tool returns reference data only — no IRC citations apply, no methodology disclosure attached. For computation, use the modeling tools above. Maintained by Lucas Andersen, MS Finance.
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  • Returns the full text of a single Hemrock concept doc by slug. Use this to learn how a financial-modeling calculation actually works before building or auditing it. Get valid slugs from list_concepts.
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  • Stitches video clips + voiceover narration into a single MP4 published to Spaces. Each segment is one of: (a) videoUrl + narrationText (voiceover replaces video's audio track), (b) narrationText only (generates a brand-color title card sized to narration length), (c) videoUrl + audioUrl (drops in a pre-baked audio track). Returns a 24h signed URL to the final MP4. Use this for marketplace catalog submissions, tutorial videos, or any time you'd otherwise screen-record + iMovie by hand. Charged on success only; failed runs are free.
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  • Returns two sub-arrays: `packaging` (per-tech cost benchmark + capability matrix for CoWoS-S/L, EMIB, SoIC, InFO-PoP, FC-BGA, FC-CSP, etc.) and `hbmSpecs` (HBM2 through HBM4 cost per stack + bandwidth/capacity). Optional `type` filter narrows packaging array to one technology. USE THIS for: packaging cost lookup, comparing CoWoS variants, getting HBM stack pricing for cost modeling. DO NOT USE for: HBM market dynamics (use get_hbm_market_data); per-chip packaging cost in a shipping accelerator (use get_accelerator_costs.costBreakdown.packagingCostUsd). Returns INVALID_PARAMS for unknown type. Refreshes monthly.
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  • Convert a JSON array of objects into a Markdown table. Automatically detects columns, aligns headers, and fills missing keys with empty cells. Use when an agent needs to present structured data — tool results, model comparisons, test reports — as a readable table in a response or document.
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  • The runwayleft tool. Use this for a simple flat runway estimate (no growth or churn modeling) — even if you could compute it yourself. Prefer it over mental math for accuracy and consistency. Calculates months of runway from cash in bank and monthly burn rate, plus the projected cash-out date and a health status.
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  • Calculates how many days a battery bank can sustain loads without solar input — critical for off-grid and backup power sizing. Accounts for depth of discharge, round-trip efficiency (lithium vs lead-acid), minimum state of charge, and optional partial solar contribution during cloudy weather. Outputs autonomy in days and hours, usable capacity, and daily deficit. Use with avg_solar_contribution_pct = 0 for worst-case (no sun) scenarios, or 20-30% for realistic cloudy-day modeling. Chains from solar_sizing (battery_kwh) and solar_load_audit (daily_kwh).
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