Tool search 103,805 tools · 5,318 live servers

List the open-source AI applications hosted and ready to run at AI NetCafé (ainetcafe.com). Each one normally requires local setup (Docker/Python + your own model API key); here they run pre-configured. Use this to find a tool for a task like translating a PDF with formulas intact, generating a PowerPoint file, polishing an academic paper, or running an autonomous research report.

Turn a topic or an outline into a real downloadable .pptx file — not a link into someone's web editor. Returns a job_id; poll check_job for the download URL. Usually 1-3 minutes. Powered by Presenton (open source) hosted at AI NetCafé.

Fetch the category-aware copy/install asset for a HeyClaude entry without writing local files. Pass assetType (e.g. 'install_command', 'config_snippet') to return only that asset and avoid the full_content/script payloads when you do not need them.

Look up who hosts a URL and where an abuse/takedown notice would go. Identifies the CDN/proxy in front (e.g. Cloudflare), the platform, or the direct host and its abuse contact. For direct hosts and previously-revealed domains it returns the real host immediately; for a domain hidden behind a proxy it explains that revealing the true host requires initiating an abuse report. Read-only; files nothing. A lookup, not legal advice; it does not guarantee removal.

Assess how a takedown for this URL would proceed: where the notice goes (host, platform, or a hidden host that must be revealed first), what documents and attestation the content owner must supply, the step-by-step process, and the legal caveats (§512(f), scope limits). Read-only; does not judge the merits of the claim and files nothing. Use resolve_host first if you only need the hosting answer.

Mesh a kernelCAD .kcad.ts source server-side and return a COMPACT geometry summary — overall bounds plus, per feature, its id, kind, triangle count, and bounding box. Use this to INSPECT a model's geometry without a viewer: confirm a part is the size/shape you expect, see how many triangles each feature contributes, or check that every feature produced geometry. This runs the full server-side OCCT pipeline (the same one the Studio renderer uses), so it evaluates modern sources (assembly, path, .material, …) that the legacy client worker cannot. INPUT: `source` (required) the .kcad.ts script text; `fileName` (optional) a label for diagnostics; `params` (optional) a map of parameter-name → number overrides applied before meshing (stateless slider recompute). OUTPUT: { ok, bounds, featureCount, features: [{ id, kind, triangleCount, bbox: { min:[x,y,z], max:[x,y,z] } }], failedFeatureIds, diagnostics }. `ok` is true when every feature meshed; `failedFeatureIds` lists features that failed to compile (and `ok` is then false). Raw vertex/index/normal arrays are NEVER returned — this is a summary only. To SEE the rendered model, use open_in_studio + get_latest_render instead.

Use this when you need to run a script and check it compiles. Run a kernelCAD .kcad.ts script and report pass/fail + feature count + diagnostics. When the scene is assembly-built (assembly().part(...) → .model()/.solvedModel()), also returns a parts summary { count, names }. Pass either { file: "<path>" } or { code: "<inline source>" }. Set { dryRun: true } for fast validation while iterating: transpile + capture + capture-light checks WITHOUT OCCT lowering, DFM gates, or meshing — milliseconds instead of seconds (100x+ on boolean/fillet-heavy scripts). A dry run catches script throws, capture-time API misuse, and assembly validity-gate failures, but NOT lowering failures or dfmSpec diagnostics; it leaves the active session untouched, so finish with a full (non-dry) evaluate_script before using session-dependent tools.

Use this when you need to see exactly what changed between two script versions. Structured geometric delta between two versions of a kernelCAD script — a baseline ({ baseFile } or { baseCode }) and a revision ({ file } or { code }). Returns agent-readable JSON: per-part added/removed/renamed/changed (volume mm³ + exact bbox deltas, numbers matching inspect({ of: 'part-stats' })), total interference-volume delta with per-pair detail, mate-graph changes (added/removed/changed mates incl. type, connectors, pose, limits), and param changes (value/min/max). Single-shape scripts diff as one "(root)" pseudo-part. Use after editing a script to verify exactly what changed physically before re-rendering. Read-only — never touches the active session.

Use this when you need to read facts about a model. One reader, selected by `of`: - 'assembly' — physical assembly inventory (parts, bboxes, connectors, mates, disconnected solids). - 'robot' — URDF/SDFormat export preview (links, joints, planning groups, end-effectors, issues). - 'step' — inspect an imported STEP file. - 'shape' — volume / surfaceArea / bbox for one feature ({ feature_id? }). - 'features' — features captured by the script (kind, id, params, transforms, suppression). - 'assemblies' — assembly intent (assemblies, parts, connectors, joints). - 'topology' — canonical face names + edge count for a feature ({ feature_id? }). - 'edges' — edges of a shape with optional EdgeQuery ({ feature_id?, query? }); returns @kc[...] refs. - 'face-edges' — boundary edges of a named canonical face ({ feature_id?, face_name }). - 'faces' — faces of a shape with optional FaceQuery ({ feature_id?, query? }); returns @kc[...] refs. - 'face-labels' — user-applied labels visible in the script. - 'mates' — mates captured by the script. - 'constraints' — sketch constraints captured by the script. - 'part-stats' — bundled parts-catalog statistics. - 'bend-table' — sheet-metal bend table for a flattened pattern. - 'params' — declared model parameters. - 'part-categories' — top-level part-catalog categories available in the bundled (and configured remote) catalog. - 'part-families' — part families within a category ({ category? }); count + exemplar ids per family. All params except `of` are subject-specific and forwarded verbatim. Most subjects accept { file | code }.

Use this when you need to check a design against a rule set. One verifier, selected by `check`: - 'assembly' — mate-aware assembly validator on the active session (run evaluate_script first). - 'urdf' — structural validity of a .urdf file ({ urdf_path }). - 'dfm' — print-readiness gates declared by dfmSpec() ({ file | code }). - 'dfm-preflight' — sheet-metal flat pattern vs a job-shop's ordering rules ({ vendor, material, thicknessIn|thicknessMm, ... }). - 'swept-collision' — sweep declared joint range(s) and report colliding poses. - 'reachable' — inverse-kinematics reachability for an end-effector ({ tip_link, target_position, ... }). - 'mounting-holes' — fastened mates expose matching hole diameters on both sides. - 'load-capacity' — closed-form Euler-Bernoulli beam stress / safety-factor check ({ loads, materials, ... }). All params except `check` are check-specific and forwarded verbatim; each check fails closed on its own missing required params.

Use this when you need to trace why a feature failed. Walk the upstream chain of a failing feature. Returns the diagnostics of the requested feature plus the diagnostics of every upstream feature in topological order (the requested feature is the last entry). Per-code hints are inline on every diagnostic — call lookup_diagnostics for the full catalogue. Pass { file?, code?, feature_id? }.

Use when you need narrative content from company filings — risk factors, MD&A, guidance language, deal terms, accounting policies, share structure. For consolidated financial numbers use run_sql on financial_statements instead. Semantic search over the full text of company-filed reports; returns matching passages. Coverage: US + Japan + Hong Kong + China A-shares. US = SEC EDGAR (including foreign issuers' 20-F/6-K). Japan = EDINET, `.T` ticker (6758.T). Hong Kong = HKEX filings, 5-digit `.HK` ticker (00700.HK). A-shares = `.SH`/`.SZ` (600519.SH, 300750.SZ). Parameters: - query (required): natural-language search; phrase it as the concept or section name you want, e.g. "share repurchase authorization", "Risk Factors". Run a few phrasings rather than one broad query. - ticker (required): US bare (NVDA), Japan `.T`, HK `.HK`, A-share `.SH`/`.SZ`, ADRs as their US symbol (SONY). - filing_types (optional): US = SEC form names (10-K, 10-Q, 8-K, 20-F, 6-K, DEF 14A, S-1/F-1, + amendments). Japan = EDINET NUMERIC codes: 120 (annual), 140 (quarterly), 160 (semi-annual). HK/A-share = plain names — annual_report; A-share quarters per-quarter (q1_report, ...); HK quarterly results all quarterly_report. OMIT to search all types. - period_start / period_end (optional): yyyy-mm window; omit to search all history. - top_k (optional): max passages to return (default 10). Scope: indexes ONLY company-filed reports — NOT institutional filings (13F-HR/13D/13G; for those use insider_and_institution_activities with source='institution'). Section targets: non-GAAP reconciliations → earnings 8-K (Ex 99.1); dilution / SBC / buyback → "Shareholders' Equity"; segment breakdown → "Segment Information"; guidance → "Outlook" in MD&A; exec comp → DEF 14A.

Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge base — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile. Coverage: US, Japan, Hong Kong, and China A-shares. `market` accepts one lowercase value or a list from `us | jp | hk | cn`; omit it or pass `[]` for all four. List order does not set priority. Pass a natural-language description (for example, "Hong Kong and China EV battery suppliers"). Returns a structured list of matching companies with context snippets. ONLY for finding a LIST of companies by description.

PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows. Hard rules (query fails otherwise): - SELECT only, no CTE (`WITH ... AS`) — use subqueries. - Period columns are TEXT, not dates — `period_end` is 'YYYY-MM'. Compare as strings (`period_end >= '2024-01'`); a `::date` cast on it fails. - Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock). Core equity coverage: US, Japan, Hong Kong, and China A-shares. Tickers are US bare (AAPL), Japan `.T` (6758.T), Hong Kong `.HK` (00700.HK), and A-shares `.SH`/`.SZ` (600519.SH, 300750.SZ). financial_statements, company_snapshot, and price_volume_history span all four. Specialized tables may be US-only or US+Japan — call get_table_schema before treating an empty result as a finding. Tables by domain (call get_table_schema for detail): - Market: price_volume_history (OHLCV history; MUST filter ticker + time_frame), index_price, equity_extended_rt (pre/after/overnight quotes) - Fundamentals: financial_statements (GAAP income/balance/cashflow), company_snapshot (ratios, per-share, growth) - Earnings: earning_call_summary, earning_call_calendar - Analyst: analyst_ratings, analyst_ratings_consensus - Ownership: insider_and_institution_activities - 8-K events: executive_change, company_deal_events, debt_issuance, securities_offering - Executives: executive_profile, executive_compensation - Alt-data: macro / industry / trade / AI-supply-chain — call list_tables(categories=[...])

Deploy a static site to a live URL — free, no account or API key required. **File content is plain text by default.** Pass HTML/CSS/JS/JSON/SVG/etc. directly in each file's `content` as a regular string. Only set `encoding: "base64"` per-file for binary content (images, fonts) — do not base64-encode text. Returns the live URL plus a claim URL (the site expires in 3 days unless claimed) — always show both to the user. To make the site private, pass `password`; always show the password to the user if you set one.

List files and directories in your persistent execution workspace (created with use_workspace=true on execute calls). Extremely useful for multi-step coding, data work, and repo-based agents. Free.

Delete a file or directory from your persistent workspace. Free. Use responsibly.

Get basic status of your persistent workspace (total size, file count, last modified). Very useful before deciding to clean up. Free.

Check if the current Warp account has a payment method on file. Call this if the user asks about their payment status, or before booking if you want to confirm they can book. Returns has_card and onboard_url if a card needs to be added.

List the agent's saved pickup/delivery locations (addresses Warp has on file for this account), so you can reuse them when booking instead of re-typing addresses. Auth required.

Returns the trust profile for a capability or solution. Call this before relying on a capability for high-stakes decisions, or when a user asks how reliable a specific check is. Returns SQS score (0-100), Quality grade (A-F), Reliability grade (A-F), execution guidance (direct, retry, queue, or fallback), 30-day test history, known limitations, and cost envelope. No API key required.

Detail for a single catalog entry — accepts a prod_ id, src_ id, or an org-scoped coordinate in the form orgSlug/slug (e.g. 'vercel/nextjs' or 'vercel/next-js'). Returns the union of product / source detail fields depending on the entry kind. Source entries list tracked CHANGELOG files by path and byte size. Pass `include_changelog: true` to inline the root CHANGELOG, or `changelog_path` / `changelog_offset` / `changelog_limit` / `changelog_tokens` to embed a specific file or slice — heading-aligned, supports per-package files in monorepos (e.g. `packages/next/CHANGELOG.md`), and emits `totalTokens` / `sliceTokens` for LLM context budgeting. Files over 1MB are flagged as truncated so you know the tail is missing.

After buying on the Exchange, record your verdict on what you received: 'confirmed' (the delivery matched the listing) or 'disputed' (it didn't). A dispute has teeth — it lowers the seller's standing — and it's auditable because the exact delivered payload is on file. One verdict per order; registered buyer + secret required.

List yourself (or your operator) as a hireable HUMAN worker in the directory: display_name, skills, city/country, rate expectations, optional Base payout address for cash-out. Owner-gated, idempotent upsert. Humans usually join via the web form at /humans/join instead.

Search 15,300+ global data center facilities across 170+ countries — by location (country/state/market), capacity (MW), operator, fiber connectivity, status (operational/under-construction/planned), or DCPI verdict. Returns name, provider, lat/lon, power_mw, fiber count, market_slug, status. Try: search_facilities country=US state=VA min_mw=10 status=operational. Use this to find EXISTING facilities; do NOT use for the forward-looking construction pipeline (use get_pipeline) or for the full profile of one facility (use get_facility).

Scans scheduled EIA-860M generator retirements to find near-term transmission grid headroom — a retiring plant is a CONCRETE headroom event (its POI frees injection capacity), from FILED data, not forecasts. Returns _entity=retirement_headroom_results: retiring generators inside your horizon (name, MW, fuel, prime mover, retirement_date), representative_point, nearest substations with distance_km + count within 25 km, county-level queue_pressure (competing in-progress MW), iso_context (the generator's own EIA balancing-authority code), and a pre-filled site_evaluation_handoff (analyze_site + get_water_risk args, capacity_mw = YOUR target load). Try: get_retirement_headroom target_mw=50 horizon_months=18 region_iso=MISO — "50 MW opening near a substation inside 18 months, sidestepping the 4-7yr mega-queue." Honesty: meta.caveat flags that filed dates are subject to ISO reliability reviews (RMR extensions). Use to find WHERE capacity opens next; for what's already queued use get_refined_queue; for one site use analyze_site.

Utility-PUBLISHED feeder hosting capacity — the MW a NAMED distribution feeder can actually take, straight from the utility's own hosting-capacity GIS. 278,799 published records across 18 utilities (Con Edison, National Grid NY/MA, NYSEG/RG&E, Rhode Island Energy, Orange & Rockland, Central Hudson, Eversource CT, BGE, Pepco/Delmarva/ACE, Dominion VA, Ameren Illinois, AEP Ohio & I&M, Xcel MN/CO, DTE, Avista). This is filed distribution-level truth, not a proximity proxy. Three ways to call it: lat+lon (+radius_km, default 25) for a point; utility or market for a whole published territory; NO ARGS for the coverage list of every market that has data. CRITICAL — check capacity_type before quoting any number: "load" = LOAD-serving headroom, what a new data-center load can actually DRAW (only Ameren Illinois, AEP Ohio & I&M and Central Hudson publish it); "gen" = DER/generation EXPORT capacity, what the feeder can ACCEPT from solar/storage — it is NOT available load and must never be relayed as "you can site N MW here"; "bus_headroom" = transmission bus MW. Returns, split by capacity_type: distinct feeder count, max + median MW, the top feeders with substation, voltage_kv, feeder_id, coords and publish date, plus the utilities publishing them. Honest by construction — published rows are GIS vertices, so distinct_feeders and geometry_rows_scanned are reported separately (never conflated), and a capacity-capped read is flagged sample_complete=false with the capacity_floor_mw at or above which the set IS provably complete. Coverage is 18 utilities concentrated in the Northeast, Mid-Atlantic and Midwest — NOT nationwide — and a point outside them returns an explicit not-published answer with the nearest covered markets, never a silent zero. Try: get_hosting_capacity utility="Ameren Illinois" capacity_type=load min_mw=5. Do NOT use for transmission-substation proximity or time-to-power (use get_grid_intelligence), the ISO interconnection queue (use get_interconnection_queue / get_refined_queue), or retiring-plant headroom (use get_retirement_headroom) — this is the distribution FEEDER layer. Informational, not binding interconnection guidance; verify with the utility.

Use when a user asks what has CHANGED in a facility's (or its market's) risk profile recently — "has this site gotten riskier lately?", "which way is this market moving?" — a temporal question static-trained models can't answer. Returns the REAL DCPI market-health delta (excess-power score change over the window, direction improving/worsening/flat) from DC Hub's history-preserving daily snapshots. INTEGRITY: only DCPI market-health has a short-term temporal series; the site-hazard dimensions (FEMA disaster / USGS seismic / NOAA climate / WRI water) are DECLARED static (they don't change week-to-week) with a pointer to the point-in-time tool — never a fabricated week-over-week delta; no snapshot history → coverage:unavailable. Params: facility_id (a discovered-facility id or slug) OR market (a market name/slug), since (e.g. "7d"/"30d", default 7d). Returns {facility, dcpi_market_health:{delta, now, direction, coverage}, static_dimensions{...}, summary}. For the current point-in-time risk (not the change) use get_composite_site_score / get_disaster_risk / get_climate_intel.

Use when a user asks to see or review their saved DC Hub shortlist in-chat (FREE with a key), or wants to know what moved on it. Example: "What sites have I saved?" / "Did any of my saved sites move?" — list_saved_sites. Params: since (optional — "24h"/"7d"/ISO, default 7d — the delta window). Returns: each saved site with name, market, lat/lon, saved DCPI score, target MW, notes — PLUS live deltas: verdict_was/verdict_now (e.g. CAUTION → BUILD), excess-power move over the window, current vs at-save DCPI, alerts armed/fired, new facilities nearby, and a `portfolio` summary flagging which sites moved and which have no alert armed. Do NOT use to add a site (use save_site) or to download the list as a file (use export_dataset); this is the in-chat read-back.

Use when a user wants to pull their saved DC Hub shortlist OUT of the platform for offline analysis, a spreadsheet, or ingestion into another tool (PRO). Example: "Export my saved sites as GeoJSON for QGIS." — export_dataset format=geojson. Params: format ("csv" default, or "geojson"). Returns: the full file contents as text — CSV rows or a GeoJSON FeatureCollection of your saved sites with DCPI score, target MW, market, coordinates, and notes. Do NOT use to list sites in-chat (use list_saved_sites) or to save a new one (use save_site); this is the bulk-download path.

Complete company information for Everstake: overview, metrics, certifications, products, clients, and contact details. Use when users need comprehensive facts about Everstake as a company.

Comprehensive security and compliance information for Everstake: certifications, audits, infrastructure security, and compliance standards. Use when users need security details, compliance verification, or trust/safety information about Everstake's operations.

Take a QBO or Xero journal-entry CSV (source auto-detected) and return a structured migration-effort estimate — row counts, unique-account count, period span, complexity classification (low / medium / high), human-hours estimate, assisted-hours estimate, and an indicative price quote in USD. Heuristic-based — refined against the live entity once the user signs up. Accepts larger files than the other analytical tools (up to 50,000 rows / 20 MB) because no detection runs here, just sizing. Use this when a user is weighing the cost of moving books to HelloBooks, pastes data and asks "how long will migration take?", "what would this cost?", or "is it worth migrating?". The funnel CTA points at /migrate/<source>?ref=<shareUrl> to start the assisted flow with the parsed sizing pre-populated.

Get an enriched company profile by ticker symbol. Returns CIK, exchange, sector, industry, market cap, employee count, description, and other fundamental data. This is a lightweight lookup (1 credit) -- use this when you only need basic company info rather than the full bundle. Always includes halted/haltCode/haltedAt trading-halt status (false/null when trading normally); a halted-but-listed ticker reports delisted:false.

Get institutional holders (13F filers) for a company. Returns institutions that hold positions in this stock based on SEC 13F filings, including shares held, portfolio weight, and filing dates. Useful for understanding institutional ownership concentration.

Search institutional investors (13F filers) by name. Returns matching institutions with CIK, name, AUM, holdings count, and latest filing period. Use this to find a specific fund or investment manager when you know part of their name (e.g., "Vanguard", "BlackRock", "Citadel"). Results are ranked by AUM descending.

Get aggregated ETF data in a single call. Combines multiple data sources (profile, holdings, sector weightings, country exposure, performance, news, analyst coverage, and comparables) into one response. Each data type is cached independently. Specify which types to include or omit to get above-the-fold defaults (profile, stock-summary, holdings, sectors).

Get the full profile for a politician including party, state, chamber, trade statistics, filing delay metrics, most traded sector, and their 10 most recent transactions. Use get_politicians first to find the slug (e.g. "sen-nancy-pelosi").

Get STOCK Act late filing violations -- trades where the disclosure was filed more than 45 days after the transaction (a legal violation). Sorted by filing delay descending. Useful for identifying politicians with poor disclosure compliance.

Returns normalized orderbook depth and liquidity profile for a specific ticker from Solana Market API data. Tickers are prediction-market event tickers (e.g. KXUSNFP-26MAY01), not spot DEX symbols. Free discovery tool. On failure returns a structured {status:"error", kind, retryable, detail} envelope.

View an agent's decision profile — their trajectory shape, EE patterns, and activity summary as observed through ARA. Paid via x402 — Trial does not cover ARA observation.

Get the full record for a single store by its numeric ID. Use after `search_stores` to retrieve fields not in the search summary (full address, owner profile, contact details). For a list of *products* in that store, call `search_products(store_id=…)` instead — this tool returns store metadata only. Read-only. No authentication. Args: store_id: Integer `id` from a `search_stores` result. Returns: A single store object with all fields. Returns ``{"error": ...}`` if the ID does not exist.

Remove a specific image from a product. Destructive, idempotent. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. Use when an image was uploaded by mistake or the merchant updated their listing. The product itself is preserved — only the image record and its file are removed. To remove the product entirely use `delete_product`. Args: product_id: ID of the product the image belongs to. image_id: ID of the image to delete. Visible in the `images` array of `get_product` responses. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: ``{"deleted": True, "product_id": int, "image_id": int}`` on success, or ``{"error": ...}`` on auth/ownership failure.

Mint a one-shot signed upload URL for a product you own. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. Use this when you have **local image bytes** (a file the user attached, bytes you generated/downloaded in your sandbox) and you want to attach them to a product that already exists. Common cases: - `create_product` returned 409 (duplicate name) — the listing already exists; this tool gives you an upload URL for it without creating anything new. - You're adding a 2nd, 3rd, … photo to a product. The returned URL is valid for ~15 min, single product, signed with your authenticated identity. From your sandbox, do **one PUT**: requests.put(result["upload_url"], data=open("/path/to/photo.jpg", "rb").read(), headers={"Content-Type": "image/jpeg"}) No auth header on that PUT — the URL is the credential. If you have a public URL (not local bytes), use `upload_product_image(product_id, image_url=...)` instead. Args: product_id: Product to attach the future image to. You must own it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: ``{"upload_url": str, "upload_expires_in": int}``, or ``{"error": ...}`` on auth/ownership failure.

Attach an image to an existing product by giving Partle a public URL to download the image from. Authenticated. OAuth (scope `products:write`) preferred; `api_key` fallback. **When to use this tool**: the image is already hosted at a public URL (a scraped product page, an Imgur link, a CDN URL the user provided). Partle's server fetches it and stores it. **When NOT to use this tool**: you have local image bytes (a file the user attached, or bytes you generated/downloaded in your sandbox). Sending those bytes through a tool argument blows past conversation context limits — phone-photo-sized payloads can be 6+ MB of base64. Instead, in your code-execution sandbox, POST the file directly to the HTTP endpoint with multipart encoding: requests.post( "https://partle.rubenayla.xyz/v1/external/products/{product_id}/images", files={"file": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Or, to create the listing and attach an image in one HTTP request: requests.post( "https://partle.rubenayla.xyz/v1/external/products", data={"metadata": json.dumps({"name": ..., "price": ...})}, files={"image": open("/path/to/photo.jpg", "rb")}, headers={"X-API-Key": "pk_..."}, ) Args: product_id: ID of the product to attach the image to. image_url: Publicly fetchable URL of the image. Server fetches it and stores it. api_key: Optional API key (`pk_*`, generate at /account). Used when there is no OAuth token, and also when the OAuth token lacks the required scope — an explicitly passed key overrides an ambient token that is scoped too narrowly. An invalid or revoked token still fails regardless. Omit when using OAuth. Returns: The created `ProductImage` record with its `id` (use for deletion) and storage path, or ``{"error": ...}`` on validation/auth failure.

Audio/video URL -> .srt/.vtt subtitle file. Premium (via x402).

Fetch the authenticated buyer's account profile + masked API key list via GET /buyer-account. Returns the enterprise_buyers row (contact_email, buyer_org, created_at, etc.) plus a list of all buyer-side API keys with masked prefixes (NEVER plaintext post-issuance — only the 12-char key_prefix is returned, e.g. 'opedd_buyer_'). Use cases: post-signup verification ('what was just issued to me?'), buyer dashboard mental model ('what licenses do I currently hold?'), audit prep ('show me the key list before rotation'). For full mid-lifecycle license details (filter_rules, billing, payouts), buyers consult the buyer portal at opedd.com/buyer. Requires OPEDD_BUYER_JWT.

Get entity metadata + recent filings for one company by CIK. Accepts canonical zero-padded CIK ("0000320193"), bare numeric ("320193"), or "CIK0000320193" prefixed. Returns full company profile (name, tickers, exchanges, EIN, SIC, addresses) plus the most-recent ~1000 filings. License: US Government public domain.

Google X-Ray search for public LinkedIn profiles via Google operators (site:linkedin.com/in). Useful when you don't want to consume LinkedIn search limits. Found profiles are saved into your contacts (in a 'Google X-Ray' list, deduplicated by profile URL) and the tool returns their contact_id values. To move them into the CRM, add them to a campaign with add_contacts_to_campaign (auto-creates CRM leads) or use a CRM tool like set_deal_stage. Paginates Google results and auto-filters duplicates.

Enrich existing contacts with their full LinkedIn profile data via the connected LinkedIn account (Unipile) — headline, location, current company & position, full experience, education and skills are scraped from each contact's profile URL and saved onto the contact (and merged into profile_data). Use after search_google_xray to flesh out lightly-saved leads. Each contact is a real LinkedIn profile view, so keep batches small; max 8 per call. Returns per-contact enrichment status.

Return the full contact profile from the database — name (with Czech vocative), headline, company, role, location, language, current campaign status and interaction history. Used as context for personalized messages or next-step decisions.

List contacts in a specific lead list with ID, name, headline, company, profile URL, gender and current status (e.g. invite_sent, connected, replied). The AI picks IDs from this list for further tools.

Check remaining daily quota for a profile. Returns current usage vs limits, ramp-up status, allowed hours, and whether actions are currently allowed. profile_id is optional — if omitted, the user's active (or first) profile is used; if no profile exists, the error response lists all available profiles.

Generate (or regenerate) an AI personalized message draft for a specific campaign_contact and step, using the template and lead profile. The message is NOT sent — it is stored as a draft with status 'pending_approval' and waits for review (via this MCP or manually). Use list_pending_approvals + approve_message to release it to the campaign executor.

Fill an Anvil PDF template (cast) with data and return the finished PDF as base64. REST: POST /fill/{castEid}.pdf. Returns { filename, byteLength, pdfBase64 }. The `data` object's keys are the template's field aliases.

Generate a brand-new PDF from HTML or Markdown and return it as base64. REST: POST /generate-pdf. For type=html, pass data = { html, css? }. For type=markdown, pass data = [ { label, content }, ... ]. Returns { filename, byteLength, pdfBase64 }.

Deploy files to a live URL. No slug → create a NEW site (works without auth; anonymous sites expire in 24h — always show the user the claimUrl). With slug → UPDATE that site (complete snapshot: send ALL files). A Dockerfile in the files makes it a server-side app (auth required; listen on process.env.PORT; persist under /data; poll app_status). Total payload ≤ 8 MB — for bigger sites use the dataecho skill scripts.

Full details + current file manifest of an owned site.

Build/run status of a container app deployed via publish_site with a Dockerfile. Poll until status is `live` or `failed`.

List files in a drive (by drive name or drv_… id), optionally under a path prefix.

Read a file from a drive. Text comes back as utf-8 `content`; binary as `contentBase64`. Files over 1 MB are refused (use the skill scripts).

Write/overwrite one file in a drive (ETag-safe: pass ifMatch to assert the version you read, otherwise the current version is used automatically).

Convert a document to Markdown synchronously (the fast lane). Decode ``content_base64`` (the raw file bytes, base64-encoded) and run markitdown over it, returning ``{markdown, meta}`` where ``markdown`` is the converted text and ``meta`` carries the source ``filename`` and the output ``length`` in characters. Best for small office/HTML/text files; for large or complex documents (or OCR-heavy PDFs) use ``submit_conversion_job`` instead.

List uploaded files belonging to your organization (fine-tune data, batch inputs/outputs, etc.). Management API: GET /v1/files.

Retrieve metadata about a specific uploaded file. Management API: GET /v1/files/{file_id}.

Get a temporary signed download URL for an uploaded file. Management API: GET /v1/files/{file_id}/url.

Permanently deletes an uploaded file from Mistral. Destructive. Management API: DELETE /v1/files/{file_id}.

Read the latest stored AI diagnosis for an annotation (root causes, confidence, suggested fix, and likely source files). Returns null when none has been generated yet; run diagnose_annotation to create one.

Run the AI Diagnosis Engine on an annotation: it analyses the captured page, element, DOM, and runtime errors to produce ranked root causes, a confidence score, a suggested fix, and the likely source files. Calls an AI provider (uses tokens / may cost money) and stores the result. Requires AI + diagnosis enabled by the workspace admin and a key set.

Discover backlink-profile competitors and prioritize overlap, authority, and link-gap research actions.

Look up a domain's agent-readiness score in the Open Agent Registry. Proxies to /open-agent-registry/api/scan. Returns the full Profile (signals, score, label, approval_path).

Outdoor delay & disruption risk score. Combines 7-day precipitation history, NRCS soil characteristics (drainage class, hydrologic group), ground-drying dynamics, temperature, freeze/thaw state, and wind forecast into a single 0–100 disruption risk score with per-day breakdown and contributing factors. Purpose-built for scheduling decisions (construction ground work, outdoor events, logistics, drone flights). Select an activity profile — ground_work | outdoor_event | logistics | aerial — to weight factors. US coverage only. [PAID: $0.25 USDC per call via x402 on Base. First call without payment_signature returns the payment requirements.]

Premium wallet intelligence and profiling for Base, Ethereum, and Sepolia. Checks address profile, EOA vs smart contract, ERC-20 token balances (USDC, USDT, WETH, LINK, etc.), total transaction counts, activity classification, and behavior tags (whale, active-trader, stablecoin-holder). [PAID: $0.1 USDC per call via x402 on Base. First call without payment_signature returns the payment requirements.]