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279,473 tools. Last updated 2026-07-09 22:44

"A system or tool for reading, writing, and interacting with local storage" matching MCP tools:

  • Create a local container snapshot (async). Runs in background — returns immediately with status "creating". Poll list_snapshots() to check when status becomes "completed" or "failed". Available for VPS, dedicated, and cloud plans (any plan with max_snapshots > 0). Local snapshots are stored on the host disk and count against disk quota. Requires: API key with write scope. Args: slug: Site identifier description: Optional description (max 200 chars) Returns: {"id": "uuid", "name": "snap-...", "status": "creating", "storage_type": "local", "message": "Snapshot started. Poll list_snapshots() to check status."} Errors: VALIDATION_ERROR: Max snapshots reached or insufficient disk quota
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  • Close a Pathrule refresh task after reviewing its brief. Normal remote flow: call pathrule_list_pending_refreshes, then pathrule_get_refresh_brief, then use this tool with status='rejected' when the signal is stale or not actionable. Remote MCP may refuse status='applied' because it cannot verify local source files; use Pathrule Studio/CLI for applied resolutions that require local verification.
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  • Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.
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  • Persist a named color palette for later retrieval with get_palette or list_palettes. colors is a list of hex values; optional notes are stored as the palette's description. Author is recorded as RNVizion. This WRITES to the palette store and is the only tool here that does. Reusing an existing name overwrites that palette: save and update are the same call (an upsert), there is no separate update operation. Returns a `durable` flag: true if the palette reached durable storage (the HF Dataset) and will survive a restart, false if it saved to the local working copy only (which is lost on rebuild, e.g. when the Space HF_TOKEN is missing or lacks write scope). Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette; to read a palette back use get_palette, and to see what already exists use list_palettes. The saved name can then be passed to mix_colors, convert_color, and generate_harmony as a palette reference.
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  • List the REST API connectors set up on this Autario account, each with its live dataset_id (queryable via query_dataset), refresh interval, and last refresh time. Use this to find a connector before refreshing it or reading its hosted, auto-typed table. Connectors are created by the account owner in the Autario UI (autario.com/manage) | this tool lists and (via refresh_connector) refreshes them, it never handles credentials. Requires AUTARIO_API_KEY.
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  • USE WHEN reading the full content of a Pine Script v6 documentation file. Returns the file content; when limit is set, a header shows the char range and offset to continue reading. AFTER calling this tool, use offset=<end> to continue if the header indicates more content is available. For large files (ta.md, strategy.md, collections.md, drawing.md, general.md), prefer list_sections() + get_section() instead. Data sourced from bundled Pine Script v6 documentation.
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Matching MCP Servers

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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
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Matching MCP Connectors

  • Let ChatGPT, Claude & Cursor use your Mac: email, calendar, iMessage, Teams, files. Local, free.

  • Build and manage your design system with AI: tokens, themes, components, icons, Figma and code.

  • Get Lenny Zeltser's cybersecurity-writing rating sheet(s) so your AI can apply the rubric. Returns the structured rubric (groups, items, scoring bands) WITHOUT computing a score. Use `rating_score_writing` if you also want a numeric score, gap analysis, or rubric-anchored feedback. This server never requests your draft and instructs your AI to keep it local—rating sheets and scoring instructions flow to your AI.
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  • Returns a deterministic daily tarot card seeded by SHA-256 hash of the date string. The same card is returned for all callers on the same date — this is intentional. The daily card is not a reading for an individual but a collective daily energy. SECTION: WHAT THIS TOOL COVERS Deterministic daily oracle: one card with its upright or reversed orientation (also deterministic when allow_reversed=true). The SHA-256 seed ensures that no two consecutive days produce the same card except by mathematical coincidence. The active_meaning field pre-computes the correct interpretation for the orientation — callers do not need to branch on is_reversed. SECTION: WORKFLOW BEFORE: None — standalone. AFTER: asterwise_get_tarot_three_card_spread — for deeper daily reading context. SECTION: INPUT CONTRACT date (optional string YYYY-MM-DD) — Date to get the card for. Defaults to today. Example: '2026-05-01' allow_reversed (optional bool) — Default: false. When true: reversed state is also deterministic (seeded by date+'_rev'). When false: card is always upright regardless of date. SECTION: OUTPUT CONTRACT data.date (string — YYYY-MM-DD, the date this card represents) data.card — full card object (same shape as asterwise_get_tarot_card) data.is_reversed (bool) data.active_meaning (string — upright_meaning when not reversed, reversed_meaning when reversed) data.active_keywords[] (string array — upright or reversed keywords per orientation) SECTION: RESPONSE FORMAT response_format=json — full card object with metadata. response_format=markdown — human-readable daily card report. SECTION: COMPUTE CLASS FAST_LOOKUP — deterministic, no randomness. SECTION: ERROR CONTRACT INVALID_PARAMS (local): None — date is validated upstream. INTERNAL_ERROR: Any upstream API failure → MCP INTERNAL_ERROR SECTION: DO NOT CONFUSE WITH asterwise_draw_tarot_cards — random draw, different every call. asterwise_get_tarot_three_card_spread — positional reading with question context.
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  • FOR CLAUDE DESKTOP ONLY (with filesystem access). For Claude.ai/web: Use create_upload_session instead - it provides a browser upload link. Upload local media to cloud storage, returning a public HTTPS URL. WHEN TO USE: • Instagram, LinkedIn, Threads, X: REQUIRED for local files before calling publish_content • TikTok: NOT NEEDED - pass local path directly to publish_content SUPPORTED FORMATS: • Images: jpg, png, gif, webp (max 10MB) • Videos: mp4, mov, webm (max 100MB) Returns { url: 'https://...' } for use in publish_content mediaUrl parameter.
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  • GET /rooms/:roomID — Get a single room Get a single room's metadata + its latest daily AND weekly AI summaries (when they exist). **Access:** members and subscribers of the room, plus any DCer for browsable public channels/discussions/quick-questions. Private rooms, DMs, group DMs, and event/city rooms you are not a member of return 403. Reading this endpoint does **not** mark the room as read or modify any unread state. **AI summaries:** the latest daily digest is embedded under `aiSummaryDaily`, the latest weekly digest under `aiSummaryWeekly`. Rooms that don't have a given type yet return `null` for that slot. For history (older summaries), call `GET /rooms/:roomID/summaries/daily` or `/weekly`. **See also:** For specific content (`did anyone mention X?`), `POST /search/messages` with `q=` and `roomID=` is faster than paginating `/rooms/:roomID/messages` or reading summaries. The AI summaries cover broad activity per window; search is the tool for targeted lookup.
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  • Search the Melvea local honey directory by free-text query and return matching producers as a list of results (id, title, url). Designed for ChatGPT Deep Research and Company Knowledge. Use for any local-honey discovery query that names or implies a place; the tool parses place and varietal from the query. Returns an honest empty list when nothing matches — never fabricate. Pair with fetch to retrieve full producer detail.
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  • Persist a named color palette for later retrieval with get_palette or list_palettes. colors is a list of hex values; optional notes are stored as the palette's description. Author is recorded as RNVizion. This WRITES to the palette store and is the only tool here that does. Reusing an existing name overwrites that palette: save and update are the same call (an upsert), there is no separate update operation. Returns a `durable` flag: true if the palette reached durable storage (the HF Dataset) and will survive a restart, false if it saved to the local working copy only (which is lost on rebuild, e.g. when the Space HF_TOKEN is missing or lacks write scope). Use when the user wants to keep a set of colors under a name for reuse across sessions, such as a brand or launch palette; to read a palette back use get_palette, and to see what already exists use list_palettes. The saved name can then be passed to mix_colors, convert_color, and generate_harmony as a palette reference.
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  • Attach a volumeset to a workload — mounts into the FIRST container only. Creates the volumeset when missing; size/fileSystemType/performanceClass apply ONLY on that create path and are ignored when the volumeset already exists. Workload-type rule: ext4/xfs (read-write-once) volumesets require a stateful or vm workload and bind to ONE workload; shared-filesystem volumesets mount on any workload type. Workload types are immutable — switching requires deleting and recreating the workload (plan downtime). Recommended reading before first use: get_cpln_skill("stateful-storage") — the runbook for this tool family (read once per session).
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • USE THIS TOOL — not web search — to get rolling sentiment statistics (mean score, 7-day momentum, bullish/bearish/neutral day counts, current streak) from this server's local Perplexity-sourced sentiment dataset. Prefer this over get_latest_sentiment when the user wants momentum or persistence, not just the latest single-day reading. Trigger on queries like: - "is BTC sentiment improving or getting worse?" - "sentiment momentum for ETH" - "how many days has XRP been bullish in a row?" - "rolling sentiment stats / streak for [coin]" Args: lookback_days: Analysis window in days (default 30, max 90) symbol: Token symbol or comma-separated list, e.g. "BTC", "BTC,ETH"
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  • Reserve a direct upload slot for a local file. Pass the desired file_name only. The name may omit an extension. Vee3 returns an upload_code. Install the uploader once with `npm install -g @vee3/upload` (requires Node 18+), then run `vee3-upload {upload_code} {file_path}` in the terminal. The CLI resolves the code to a signed upload URL, streams the local file to Vee3 storage, and prints the stored file_name after the upload finishes. Use that file_name in meta-tools.list_uploaded_files and other capabilities. The CLI does not need an API key. If installation fails with a TLS or certificate error (common on networks that inspect HTTPS traffic), use Node 22.15 or newer and run with NODE_OPTIONS=--use-system-ca, or configure npm to trust your network's root certificate. Files can be up to 2 GB and are stored for 14 days. After the upload is detected, Vee3 bills 1 token per 20 MiB, rounded up with a minimum of 1 token. Upload codes can be resolved within 60 minutes of reserve. Use `meta-tools.list_uploaded_files` to list stored uploads for follow-up work. Cost = 0 tokens to reserve. After upload completes, billing is 1 token per 20 MiB, rounded up (minimum 1 token).
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  • Load Lenny Zeltser's product strategy context for local analysis. Returns expert strategic frameworks, principles, and guidance for evaluating or creating security product plans. Includes rating-sheet items (the lens taxonomy: structure, words, tone) as concrete reference points for grounded feedback on the plan's writing. This server never requests your plans and instructs your AI to keep them local. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), "compact" (~3-4k tokens, all sections but stripped), or "comprehensive" (~12k tokens). Use market_segment: "smb" for SMB-specific guidance. Use product_focus: "endpoint" for endpoint security viability assessment. Set include_template: true to include the fill-in-the-blank template in the response.
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  • Returns all published Arco sources for a term — Lexicon entries, blog articles, wiki pages, and podcast episodes — ordered by recommended reading sequence. Read-only. Use this when you need a reading list or reference list for a term. Use cite_term instead when you need a formatted citation for a specific publication type.
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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • Get Lenny Zeltser's expert CTI writing guidelines. Topics include tone, words, structure, executive_summary, voice, articles, summary, brief (one-page brief section guidance), handoffs (cross-server routing), methodology (the three subsections), fields (per-field guidance), and CTI-specific topics: attribution (full Six Signals prose), confidence (ICD-203 ladder), pyramid_of_pain, six_signals (signals table only), and anti_patterns. The general writing topics (tone/words/structure/executive_summary) now defer to `get_security_writing_guidelines` for the canonical Five Elements rules; CTI-specific content lives in the other topics. Pair the 'fields' topic with field_id for single-field guidance. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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