"Information about SVG (Scalable Vector Graphics)" matching MCP tools:

• mio_image_png_to_svg

  MiOffice — AI-Powered Workspace Studio

  PNG to SVG — Convert raster images to scalable vector graphics. Runs in the browser. Covered by signup welcome credits and by the Day Pass (24-hour unlimited on this workspace group). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

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• get_safety_features

  Makuri Showcase (CogniLedger)

  Returns information about safety features on Makuri, including age verification, content filtering, parental controls, and AI safety guardrails. Use when the user asks about child safety, content moderation, or how Makuri protects minors.

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• emem_state

  emem — Earth memory protocol

  Get one dense numeric fingerprint that summarises everything known about a place — ready to feed into similarity search, a classifier, or clustering. Two views: `encoder` returns a single AI-model embedding (128-D Tessera, 1024-D Clay, 1024-D Prithvi); `cube` returns the full 1792-D vector concatenated across every band, with a per-band coverage manifest. When to use: Call this when the user wants a machine-usable summary of a place rather than individual band readings — e.g. 'give me a feature vector for this location', 'how do I represent this place for ML', or before running similarity / linear-probe / clustering downstream. Also use it to get one rebindable handle (`memory_token` / `state_cid`) that cites the whole place. Default `view=encoder` is the cheap single-recall path; pass `view=cube` for the full attested view (its `coverage[]` lets you tell signed-zero from not-yet-materialised). Then hand the vector to `emem_find_similar` (k-NN), `emem_compare` (two-place cosine), or `emem_verify_receipt` (audit the signature).

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• get_business

  Venturu

  Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.

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• get_cvss_details

  ContrastAPI

  Parse a CVSS v3.x vector string into a per-metric breakdown plus a recomputed base score. Returns the canonicalized vector, version (3.0 or 3.1), base_score, base_severity (NONE/LOW/MEDIUM/HIGH/CRITICAL), and the eight base metrics: attack_vector (NETWORK/ADJACENT_NETWORK/LOCAL/PHYSICAL), attack_complexity (LOW/HIGH), privileges_required (NONE/LOW/HIGH), user_interaction (NONE/REQUIRED), scope (UNCHANGED/CHANGED), and the three impact metrics confidentiality_impact / integrity_impact / availability_impact (NONE/LOW/HIGH each). When temporal/environmental metrics are explicit in the vector, temporal_score and environmental_score are populated separately. Use to translate raw CVSS strings into agent-friendly attributes without re-parsing the vector grammar yourself, and to verify upstream NVD scoring against the recomputed value. v2 vectors (AV:N/AC:L/Au:N/...) are rejected with 400 — read cvss_v2_vector from cve_lookup if you need v2 detail. Free: 30/hr, Pro: 500/hr. Returns {version, vector, base_score, base_severity, metrics: {attack_vector, attack_complexity, privileges_required, user_interaction, scope, confidentiality_impact, integrity_impact, availability_impact}, temporal_score, environmental_score, summary, verdict}.

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• data.capabilities

  Recursive Support Oracle

  Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.

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• upload_asset

  mcp

  Upload an asset (image, font, PDF, etc). Provide exactly one of: content (base64), content_text (plain text for JS/CSS/JSON/SVG — preferred, saves tokens), or source_url (public HTTPS URL for images). Set overwrite: true to replace an existing asset.

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• search_icons

  Supericons

  Search 20,000+ curated SVG icons across 10 libraries by meaning, label, visual description, tags, and synonyms. Use this when the user describes an icon concept such as "database", "user profile", "chill", "security", or "AI model". Returns matching icons with SVG code and public semantic guidance.

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• get_icon

  Supericons

  Retrieve one exact SVG icon when the icon ID and library are already known. Use search_icons first if the user only described a concept. Returns SVG code and public semantic guidance for the exact icon.

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• record_drives_drift

  space0

  Apply a clamped (±0.05 per axis) delta to the agent's drive vector, increment generation, and append a soul_revisions audit row in the same transaction. Use after a reflection produces a drift signal. Returns the new drive vector and generation.

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• patch_asset

  mcp

  Apply targeted text changes to an existing asset (js, css, json, svg) without re-uploading the full file. Uses find/replace like patch_page. For binary assets (images, fonts), use upload_asset with overwrite: true instead.

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• emem_coverage_map

  emem — Earth memory protocol

  Live SVG render of the responder's corpus density, returned as a proper MCP EmbeddedResource content block (image/svg+xml) — multimodal MCP agents can render it natively. When to use: Call when the user asks 'where do you have data?', 'show me the coverage', or wants a visual brief of the responder's corpus footprint. Returns a 1440×720 Plate-Carrée SVG (1° × 1° bins, log-scale colour, continent envelopes for orientation) plus a structuredContent summary (cell_count, total_facts, responder pubkey, REST URL). Multi-content-block reply: an EmbeddedResource (mimeType `image/svg+xml`, with text + uri) followed by a one-line text summary so text-only clients still see the cell / fact counts. For the bare image bytes, fetch `/v1/coverage_map.svg` over plain REST.

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• add_image

  cnvs.app

  Place a raster or SVG image on the board at (x, y) with explicit width/height in board pixels. `data_url` MUST be a `data:image/(png|jpeg|gif|webp|svg+xml);base64,...` string ≤ ~900 kB; hosted URLs are not accepted. Strongly recommended: also pass a tiny `thumb_data_url` (≤8 kB JPEG/PNG/WebP, ~64 px on the long edge) — it is embedded into the SVG preview so OTHER AI viewers (and you, on later `get_preview` calls) can actually see the image instead of a placeholder box.

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• chunk_text

  Toolora MCP Server

  Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.

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• chunk_text

  Toolora

  Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.

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• ask_alti

  mcp

  Ask Alti, Christian Perez's AI agent, a single question about Christian — his work at Altivum, The Vector Podcast, his book 'Beyond the Assessment', his military service as a Green Beret, or his AWS / Applied AI engineering practice. Returns a concise 2-4 sentence reply grounded in Christian's published writing and autobiography. Does NOT answer general knowledge questions.

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• get_preview

  cnvs.app

  Compact schematic SVG render of the board (typically a few kB even for dense boards). Returns both an image/svg+xml content block (you can SEE it) and the raw SVG text. CALL THIS any time you need to understand where things are — before placing new items, before deciding whether the canvas is crowded, before picking a free region. AI-authored items get a purple border so you can tell which contributions were yours. For precise text content prefer `get_board`.

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• pentest_guide

  pentest-mcp-server

  Return a structured attack methodology playbook for the given attack vector and optional target context, for use in authorized penetration testing, CTF, or security research. Covers reconnaissance, enumeration, exploitation, and post-exploitation phases for the vector, filtered to what is relevant given the provided stack and WAF profile. Each phase includes: what to look for, tools to use, common mistakes, detection indicators that would alert defenders, and recommended mitigations. Next-tool suggestions are pre-filled with payload generator and technique lookup calls. Covers 15 vectors via the vector enum. Authorized testing only.

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• get_vaadin_primer

  docs-mcp

  IMPORTANT: Always use this tool FIRST before working with Vaadin. Returns a comprehensive primer document with current (2025+) information about modern Vaadin development. This addresses common AI misconceptions about Vaadin and provides up-to-date information about Java vs React development models, project structure, components, and best practices. Essential reading to avoid outdated assumptions. For legacy versions (7, 8, 14), returns guidance on version-specific resources.

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• get_trip_details

  sbb-mcp

  Get detailed information about a specific train connection including all intermediate stops, platforms, and occupancy. Use a trip ID from search_connections results.

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