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742,106 tools. Updated 2026-11-04 13:08

"A resource for finding specific high-resolution images online" matching MCP tools:

  • Upload a base64-encoded file to a site's container. Use this for binary files (images, archives, fonts, etc.). For text files, prefer write_file(). Requires: API key with write scope. Args: slug: Site identifier path: Relative path including filename (e.g. "images/logo.png") content_b64: Base64-encoded file content Returns: {"success": true, "path": "images/logo.png", "size": 45678} Errors: VALIDATION_ERROR: Invalid base64 encoding FORBIDDEN: Protected system path
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  • Discover the investment-thesis catalog. Each entry is a descriptive case study that pairs an economic framework with a rule-based portfolio and the synthetic + historical stress evidence for that allocation. Returns one compact summary per thesis (slug, title, one-liner, tags, risk tiers, framework summary, headline finding). Call get_investment_thesis(slug) for the full framework / portfolio / stress evidence, or read the thesis://{slug} resource. Descriptive, not advisory — the agent decides what is suitable.
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  • Read attached evidence through MCP without changing its format. Pass evidenceId from goal-get. Text (text/plain, JSON, NDJSON) returns newline-preserving redacted lines; offset/limit are zero-based line pagination. Images return a native MCP image with original MIME and bytes. For a complete video, PDF, ZIP or other binary, binaryDelivery=link (default) returns a resource_link to the authenticated original download — no base64 and no conversion. If the client cannot open external links, binaryDelivery=base64 embeds the exact original bytes in a resource blob; this expands data by about 33% plus JSON overhead and can consume the client context window, so use it only when needed. byteOffset/byteLimit require binaryDelivery=base64. Text secrets are redacted; binary evidence is unmodified.
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  • Read attached evidence through MCP without changing its format. Pass evidenceId from goal-get. Text (text/plain, JSON, NDJSON) returns newline-preserving redacted lines; offset/limit are zero-based line pagination. Images return a native MCP image with original MIME and bytes. For a complete video, PDF, ZIP or other binary, binaryDelivery=link (default) returns a resource_link to the authenticated original download — no base64 and no conversion. If the client cannot open external links, binaryDelivery=base64 embeds the exact original bytes in a resource blob; this expands data by about 33% plus JSON overhead and can consume the client context window, so use it only when needed. byteOffset/byteLimit require binaryDelivery=base64. Text secrets are redacted; binary evidence is unmodified.
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  • Retrieve one complete prepared resource profile, including evidence-backed facts and primary-source provenance, by its stable resource ID.
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  • Returns the plain-language meaning and step-by-step fix for one Malinois finding. Use it while helping the user fix an issue reported by scan_app, or when they ask what a finding means. Pass the rule_id exactly as scan_app returned it. Read-only, no network, instant.
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  • Read-only access to published High Signal updates. Retrieve signals for an India Standard Time day and fetch the linked evidence for a specific signal.

  • Generate images with the catalogue's image model, returned inline; image price plus $0.01 a call.

  • Get a one-time upload link for a LOCAL file to attach to create_website / edit_website. MCP cannot carry files, so a local file goes straight from disk to Grigora's storage with the returned `curl` command (replace <LOCAL_FILE_PATH> with the file's path and run it in a shell). The file's contents never pass through the conversation. Then put the returned `url` in the attachments list of create_website or edit_website. The link expires in 15 minutes; one link per file. Allowed: images (PNG, JPG, WebP, GIF, AVIF), PDF, CSV (up to 10 MB), and audio/video (up to 80 MB). For a file that is already online, skip this and pass its public URL directly. Args: file_name: The file's name, e.g. "brand-guide.pdf" (refer to it by this name in the prompt). mime_type: e.g. "image/png", "application/pdf", "text/csv", "video/mp4". size_bytes: The file's exact size in bytes (e.g. from `wc -c < FILE`).
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  • Apply a post-hoc triage verdict to a finding that was previously recorded via record_finding. Used by the /reply-to-code-review flow to persist whether a finding is TRUE / FALSE / UNCERTAIN and the FIX / DEFER / IGNORE action taken. The finding is located only by the exact `finding_id` returned by list_pr_findings, on ANY lifecycle status (open, fixed, or dismissed — so verdicts still apply after a PR is merged and findings were swept to dismissed). Only findings recorded into the data layer (the aictrl-dev MCP path) can receive a verdict. Idempotent: re-applying overwrites the prior verdict. A not_found response is an application error; call list_pr_findings to refresh stale IDs and do not treat the write as successful. `judged_at_sha` is required: send the full 40-hex commit SHA of the code you actually read. A SHA that is neither the review SHA nor a later commit of the same PR is rejected with validation_error. `reasoning` is required too (#5364): a verdict whose reasoning cannot be audited later is not worth storing. Each write appends to the finding's judgment history; a re-judge from the same run at the same commit updates that run's own row rather than appending a duplicate. A FALSE verdict on an OPEN finding of severity MINOR or NIT (medium/low/info) also dismisses it as a false positive, with your `reason` as the note; on MAJOR or BLOCKER (high/critical) it stays a suggestion a person confirms. The result reports `autoDismissed` (and `autoDismissReason` when false). A dismissal is not reopened by this tool; a person can restore the finding from the pull-request page.
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  • Retrieve The Hill Kinabalu’s official current room catalogue, including room types, indicative weekday and weekend rates, guest capacity, beds, amenities, unit counts, images, and booking links. Use this when someone asks which rooms The Hill Kinabalu offers or what its room rates are. This catalogue does not check availability for specific dates.
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  • Read a registered server resource URI, not an ordinary web URL. USE WHEN you have a judgment://, legislation://, hansard://, or server:// URI returned by this server. Do not use for https:// URLs; use the source-specific tool instead (for a canonical GOV.UK HMRC internal-manual URL, call hmrc_get_manual_page). Returns the resource content as a string. Binary content is base64-encoded. AFTER calling, use the returned primary-source content and URI in citations; if the URI is rejected, follow the named source-specific tool rather than treating the URL as retrieved evidence. Source: registered UK Legal MCP resource providers.
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  • Read a registered server resource URI, not an ordinary web URL. USE WHEN you have a judgment://, legislation://, hansard://, or server:// URI returned by this server. Do not use for https:// URLs; use the source-specific tool instead (for a canonical GOV.UK HMRC internal-manual URL, call hmrc_get_manual_page). Returns the resource content as a string. Binary content is base64-encoded. AFTER calling, use the returned primary-source content and URI in citations; if the URI is rejected, follow the named source-specific tool rather than treating the URL as retrieved evidence. Source: registered UK Legal MCP resource providers.
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  • Get full specifications, equipment, all images, and pricing per term for a specific vehicle. Use a vehicle_id from search_vehicles results. IMPORTANT: Always show `detail_url` as a clickable link — it points to the FINN configurator where the user picks term and km. To produce a direct checkout link for a specific term + km combination (and optionally a one-time Fahrzeugbereitstellung), call `get_subscription_pricing` and use the `checkout_url` it returns. Never construct checkout URLs yourself. The `vehicle_id` field is an internal API identifier — never display it to users.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Scan a public GitHub MCP-server repository for security issues. Clones the repo (shallow, <60s, <200 MB), runs compuute-scan v0.6.2 in static analysis mode (no code execution from the target), and returns a structured report with severity counts, a 0-100 score, and the 10 most severe findings. WHEN TO USE: - Before connecting to an unknown MCP server discovered via Anthropic Registry, Smithery, mcp.so, or a Discord recommendation. - Before installing a third-party MCP-server package into a production pipeline. - As part of an agent's pre-commit / pre-deploy due-diligence step when adding new dependencies. - As one input to a multi-source trust evaluation (combine with publisher reputation, package install count, last-update recency). WHEN NOT TO USE: - For private repos. Use the on-prem CLI instead: `npx compuute-scan ./path-to-private-repo` - For deep exploitability assessment of a specific code path. This is pattern matching, not dataflow analysis. Book a manual L2-L4 audit at https://compuute.se/audit for that depth. - For non-GitHub hosts (GitLab, Bitbucket, self-hosted). v1 supports github.com only. - For repos > 200 MB or clone time > 60s. The endpoint returns a 413 or 504 in those cases — fall back to local CLI. EXPECTED RESPONSE TIME: - Median: ~1-2 seconds for small repos (<100 files). - p99: ~10 seconds for medium repos. - Hard timeout at clone=60s, scan=120s combined. EXPECTED COST: - Free tier in MVP. Future Pro tier may charge per-scan or per-month. DATA FRESHNESS: - Scanner version is reported in response.scanner.version. - L1 rule set freshness reflects compuute-scan releases — see github.com/Compuute/compuute-scan/CHANGELOG.md for the latest CVE and threat-intel response timeline. EXAMPLES: Example 1 — scan an MCP server you're evaluating: github_url = "https://github.com/modelcontextprotocol/servers" → score: 0, summary: {critical: 1, high: 94, medium: 22} → top_findings include SSRF, eval, etc. → recommendation: "AVOID — 1 critical and 94 high finding(s)..." Example 2 — scan a clean reference implementation: github_url = "https://github.com/microsoft/azure-devops-mcp" → score: 90+, summary: {critical: 0, high: 1} → recommendation: "REVIEW — 1 high finding(s)..." Example 3 — scan your own dev MCP-server before publishing: github_url = "https://github.com/yourorg/your-mcp" → audit your own surface before others install it OUTPUT FIELDS (stable schema): - repo_url (str): canonical URL of the scanned repo. - score (int): 0-100, higher safer. Coarse summary, not a precision claim. - summary (object): {critical, high, medium, low, info, files_scanned}. - recommendation (str): action guidance derived from severity counts. - findings_count (int): total raw findings (may include false positives). - top_findings (list): up to 10 most severe, each with {id, title, severity, file, line, owasp, cwe}. - l0_discovery (object): MCP transport, tool count, dependency pinning. - performance (object): clone_seconds, scan_seconds, repo_size_bytes. - scanner (object): {name, version, layers_covered}. - _disclaimer (str): MANDATORY triage disclaimer. Read it. Args: github_url: Public GitHub HTTPS URL (e.g. https://github.com/org/repo). Must be public and < 200 MB. v1 is github.com only. Returns: Structured scan result. On error, returns {"error": code, "message": ...} with HTTP-style code (invalid_url, clone_failed, scan_timeout, etc.).
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  • Scan a QuickBooks Online "Journal Entries" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Round numbers are statistically rare in real bookkeeping and frequently indicate estimates, plugs, or fraud signals worth review. Input is raw CSV text from QBO Reports → Accountant → Journal. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes QBO data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Tier-0 subset — HelloBooks Phase 3.0 anomaly detection in the paid product additionally catches GL outliers vs entity history, vendor-history mismatches, archived-vendor activity, and AI-narrated suspicious lines (which require the live HelloBooks account).
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  • Scan a QuickBooks Online "Journal Entries" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Round numbers are statistically rare in real bookkeeping and frequently indicate estimates, plugs, or fraud signals worth review. Input is raw CSV text from QBO Reports → Accountant → Journal. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes QBO data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Tier-0 subset — HelloBooks Phase 3.0 anomaly detection in the paid product additionally catches GL outliers vs entity history, vendor-history mismatches, archived-vendor activity, and AI-narrated suspicious lines (which require the live HelloBooks account).
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  • Resolve free text to a canonical market or macro entity. Turns a ticker, company name, macro indicator, coin, or currency pair into the agent plane's ``{namespace, ids}`` entity for use with get_snapshot and get_timeseries. A cross-namespace collision (e.g. a ticker that is both an equity and a coin) returns status "ambiguous" with ranked candidates and NEVER silently picks one; pass type_hint (e.g. "equity", "etf", "coin") to narrow the universe. Crypto aliases resolve too (e.g. "bitcoin" -> the BTC coin entity). Status "low_confidence" means the best match cleared resolution but scored weakly - verify the returned entity before building on it, or re-query with a more specific name or type_hint. For compliance KYB lookups by LEI/VAT or sanctions screening use sugra_entity_lookup / sugra_entity_screen instead - this tool is for market-data entities. Args: query: Free-form text - ticker, company, indicator, coin, or pair. type_hint: Optional namespace hint narrowing resolution.
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  • Long-poll subscription that pushes ctx.info() on each new inbox file. Replaces bash polling daemons (watch-relay-*.sh) with server-initiated push. Call once at session start (e.g. via SessionStart hook). Server holds the subscription, watches the calling agent's role-specific inbox dir, and fires info-level notifications on each new relay file arrival. Client re-calls this in a loop for persistent coverage. Per PR #1 (CCR-inversion-for-relay-pickup): `inbox_filter` parameter added to BYPASS role-based dir resolution. Use when role detection is unreliable OR when subscribing to a specific canonical inbox (e.g., 'cc_tb'). Closes 3-week-old feedback_relay_arrival_invisible_midsession HARD RULE.
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  • Multi-carrier LTL comparison — returns 30+ carrier rates ranked by price (slow, ~15s). Call IMMEDIATELY AFTER ltl_quote with the same parameters; this fills in the 'finding other carrier rates…' section the fast quote card was showing. Useful when the user wants to compare carriers or pick a specific one. Do not declare a winner or recommend a specific carrier; just present the ranked list.
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  • Convert one base64-encoded image to PNG, JPEG, WebP, or AVIF. Use input_mime_type with a real image MIME such as image/png or image/jpeg; common aliases like image/jpg, jpg, png, svg, and application/octet-stream with a filename are accepted. Use the REST API for source images larger than 5 MB. On every call, pass telemetry.agent_thinking with your reasoning for this specific call. Pass telemetry.user_intent only on the first tool call after a new user message.
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  • Generate a cohesive SET of custom images on one SOLID-COLOR background or a TRANSPARENT one, each one a separate isolated subject sharing one visual style (icons, logos, game assets, UI elements, sprite/asset packs; transparent for images that drop onto any backdrop). The style parameter says how everything is drawn; the subjects parameter says what to draw; the background parameter is a color or "transparent". The style can also come from reference images via the styleReferences parameter - alone, or best combined with the style text (text plus references holds a style tightest). Returns a zip download URL. Cost: 1 credit per call. When a solid color fits the user's use case, it is the faster choice. Run generation calls sequentially, never in parallel - only one generation runs at a time per API key. For composed, full-bleed pictures (scenes, hero images, banners, posters, environments), use generate_illustration_set instead. For several images of ONE character (the same mascot, creature, person, or product in different poses or moods), use generate_character_set instead. For many different ideas from one brief, each in its own style (logo ideas, mascot concepts), use generate_concept_set instead. For ONE logo shown many ways, use generate_logo_variations instead. Output formats: PNG (lossless), JPEG, or WebP; JPEG has no alpha channel, so a set delivered transparent is PNG or WebP. Images can be delivered at a fixed width and height, at one fixed axis with the other hugging each subject, or at their native resolution. Size and quality considerations: Leaving width and height unset delivers images at their native resolution, unscaled under relative sizing except that a subject far larger than the rest is shrunk (fill sizing scales each subject to its frame), which produces the highest quality results and is recommended when images will be post-processed, composited, or resized downstream. On a solid background, native output dimensions vary between generations and track the subject count - roughly 650-950px per side for small sets, down to roughly 400-650 at the full 16; fewer subjects means larger native images. Fixing width and height (e.g. 512 and 512) guarantees consistent dimensions across all images and generations but applies resampling which may soften fine details; fixing one axis lets each image keep its subject's own proportion on the other. IMPORTANT - style and subject description rules for best results: The style applies to every image in the set, so it is what keeps them visually consistent. Put HOW the images are drawn (technique, palette, surface treatment) in the style, and make each subject description only about WHAT that one subject is, not how it looks. A quick test for any phrase: is it WHAT the subject is, or HOW it is drawn? HOW belongs in the style, shared across the set. - Get the style and the subject descriptions right with the user before you call. When their request puts how an image is drawn, a background, or a scene into a subject description (or names the subjects to draw in the style rather than as separate entries in the subjects list), fix it as you compose the call: routine moves of shared technique into the style you can just make, but when a change drops or alters something they explicitly asked for, tell them what you are adjusting and why first. Each call costs a credit, so it is worth getting this right up front rather than spending one on a framed or scene-filled result. - The style describes the visual treatment of the images (e.g. 'watercolor', 'pixel art', 'stained glass'). It must NOT mention background color, image count, layout, or sizing. - Do not list the subjects to draw in the style (e.g. 'illustrations of a fox, an owl, and a deer'); the style is only the shared visual treatment, and the subjects belong in the subjects list, one per entry. A category or theme word is fine (e.g. 'insect illustration'). - Do not put background color or background descriptions in the style or subject descriptions. - Avoid framing the style as a type of painted canvas ('oil painting', 'acrylic painting', 'gouache painting', 'pastel painting'). These tend to produce each image as a rectangular framed canvas with its own colored background, rather than an isolated subject. Prefer 'illustration' or a specific technique: 'watercolor illustration', 'pen-and-ink sketch', 'ink wash', 'relief-etching', 'pastel drawing', 'woodblock print'. - Avoid color-field or atmospheric phrasings in the style ('luminous backgrounds of violet, rose, and gold', 'set against jewel-tone fields', 'dreamlike rainbow atmosphere'). These instruct the image model to fill each image with colored atmosphere, producing framed compositions rather than isolated subjects. Describe only the linework, palette, and technique of the subjects themselves. - Do not describe an aged, weathered, cracked, or textured surface, ground, wall, panel, or paper that the whole artwork sits on ('on aged wood', 'cracked fresco wall', 'aged parchment surface'); name the art tradition(s) or style(s) instead ('fresco-style illustration'). Texture that belongs to a subject's own material is fine ('a weathered bronze shield', 'a cracked ceramic vase'). - No captions, labels, or annotations. Text that is part of the depicted object is fine (e.g. 'STOP' on a stop sign, 'EXIT' on an exit sign). - No grid lines, borders, frames, or separators. - No overlapping or collage-style arrangements. - Do not connect the subjects to each other or give them shared physical elements: no wires, cords, chains, ropes, ribbons, vines, or threads running between subjects, no frame or banner they share, no phrasing like 'connected by' or 'strung together', and no single continuous line or tube forming multiple subjects. Each subject must be drawable in complete isolation; connections inside one subject (a chain on an amulet, laces on a boot) are fine. - No dramatic/long drop shadows (subtle shadows are fine). - Subject descriptions should describe WHAT to depict, not where to position it. - Each image is ONE isolated subject, not a scene. Describe the subject with its pose or action and anything it directly holds, rides, or interacts with, but not the surrounding setting, environment, landscape, or sky. For composed scenes (a figure set within an environment), use generate_illustration_set instead. - Do not use size words (large, tiny, small, etc.) on the overall image subject (e.g. 'a large elephant', 'a tiny mouse') - all images are produced at the same size. Size words on details within the image are fine (e.g. 'a plate with a small insignia'). - Maximum 16 images per generation. Do not put the image count in the style. - Subjects must be distinct: entries that differ only in case, punctuation, or spacing count as the same subject and the call is rejected. Explicit filenames must be distinct too (a different extension alone is not distinct). - The style must actually describe a visual style, and each subject must name a drawable subject; text that does not is rejected. - Style description max length: 500 characters. Subject description max length: 200 characters each. - Size: width and height are separate parameters, each 256 to 512 pixels when given. Both given is an exact box; one given fixes that axis and the other hugs each subject (so images in the set differ on it, and it may fall below 256); neither given delivers native resolution, which is also the path to larger images. - Sizing: relative (the default) keeps the sizes the model gave the subjects in relation to one another, one scale for the whole set; fill scales each subject on its own to fill its frame less the margin, the icon-set convention, giving up relative size and enlarging subjects smaller than the frame (the result says by how much). Both can be changed later with edit_set. - Icons: the subject count sets how large a batch's icons can later be exported with export_set, crisp at every density: about a 136px base size with 13 to 16 subjects, 160 with 10 to 12, 180 with 7 to 9, 192 with 5 or 6, 256 with 4 or fewer. Every generation result states its batch's own crisp base size. - If the style check returns a suggested cleanup, show the user the specific changes and get their confirmation, then resubmit the approved prompt with validation set to "skip" so it generates exactly as approved (resubmitting without "skip" re-runs the check and may return further suggestions). See the validation parameter for when to use "skip" and "auto-apply". - To add more subjects to a set, call extend_image_set with the id of any batch in it, as often as the set needs. - If a "Rate limit exceeded" error is returned, wait the suggested number of seconds before retrying. Do not retry immediately. - Showing the result: as soon as the call returns, show the user every delivered image before you put them to use, then keep working without waiting for a reply (unless the user asked to review first), so they can ask for a change before anything is built on them. Show each image exactly as delivered, as its own file: the files are the product, and their exact size, margin and background are what the user asked for. Never present a new image made from them, even to check them; it hides all three. Files on disk or a link in your context are not delivery. Where you can open files on the user's machine, open the extracted index.html with the host's file opener; it shows each image at its delivered size with its dimensions. Where you can attach files to your reply, attach each delivered file as it is (attaching is not inspecting). Otherwise give the online viewer link and the zip link. Show every image unless the user asked for only some, and say in one line what you left out; if you can show none, say the set was made but you could not show it, and give the viewer link.
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