"A server related to EVE Online's MCP" matching MCP tools:

• generate_harmonyA

  rnv-color-mcpA

  Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors. Read-only and deterministic: it derives the colors from the base and stores nothing, so it has no side effects and is safe to call repeatedly. Use to expand one base color into a related set; to blend existing colors into a single color use mix_colors, and to persist a set you like use save_palette.

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• generate_harmonyA

  rnv-color-mcpA

  Generate a color harmony from a base color. base accepts a hex, CSS name, RNV brand name, or saved-palette reference (e.g. 'Spring line:2'). scheme is one of: complementary, analogous, triadic, split-complementary, tetradic (a.k.a. square), monochromatic, compound. Returns a list of hex colors. Read-only and deterministic: it derives the colors from the base and stores nothing, so it has no side effects and is safe to call repeatedly. Use to expand one base color into a related set; to blend existing colors into a single color use mix_colors, and to persist a set you like use save_palette.

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• search_ipA

  Netmon (demo)A

  Find every mention of a specific IP across Netmon's log and telemetry streams: syslog, Windows eventlog, Suricata EVE, aggregated NetFlow, and ARP. Returns one bucket per stream with {total, samples}. Streams that 4xx (e.g. 403 from tag-scope) show up in `skipped` so a partial result is still actionable. The syslog/eventlog streams match the IP via an unindexed message substring scan; on a high-volume install they can time out and land in `skipped` with guidance (narrow `hours`, or use syslog_search/eventlog_search with a device_id) rather than stalling the call. Params: - ip (required): IPv4 or IPv6 to correlate. - hours: lookback window (1-168, default 24). - per_stream: sample row cap per stream (1-100, default 10). The `total` per stream is always the full match count. - streams: narrow the fan-out to a subset — any of ['syslog','eventlog','eve','netflow','arp']. Omit for all. Permission + tag-scope checks run server-side; a tag-restricted user sees only rows for devices in their tag set. Example (narrow + short window): search_ip({ip: "10.10.1.25", hours: 1, streams: ["syslog"], per_stream: 5})

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• update_wordA

  Lexpad – Vocabulary Notebook & FlashcardsA

  Changes a word's headword, part of speech, level, topic, pronunciation, hard-to-spell mark and spelling note, usage note, corrected form, collocations, expressions, related words or the user's private note. Only the fields given change; meanings and practice progress are not touched. A headword the notebook already has is refused. The previous values are replaced.

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  Destructive

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• get_skillA

  BytesAgain AI Skills SearchA

  Fetch full details for one skill by slug. Call AFTER search_skills or popular_skills when a user selects a specific result — do NOT batch-call for every item. Returns: name, description, category, tags, version, author, downloads, stars, install_command, homepage_url, repo_url. Error lifecycle: slug not found → {error: "Skill not found"} → fall back to search_skills with related keyword. Never guess slugs; only use slugs from prior tool results.

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• get_relatedA

  ESG Hub MCP ServerA

  Traverse the ESG Hub knowledge graph one hop from a page and return every connected record grouped by edge type. Use it after get_esg_page when you need neighbouring concepts; to read a page's own content use get_esg_page. Returns at most 15 related pages and, today, only `related_pages` edges; a page with no links returns an empty group list, not an error. There is no pagination. `record_id` accepts a `page:` record ID or a permalink; `edge_type` filters the result to one edge type (default: all). Cached ~10 minutes; rate-limited per IP; retry on 5xx.

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• help_getA

  DreamLand MUDA

  The full text of one help article as Markdown, with links to related articles. Pass the id from help_search, or a keyword: an exact title wins, a keyword several articles share returns them to pick from, anything else gets the best search hit.

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• get_nursing_diagnosisA

  CarePlanKit — Nursing Care PlansA

  Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.

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• combined_trends_toolA

  SantimentA

  Combined trends tool that fetches trending words, stories, and documents in parallel. This tool provides a unified view of all trending data - words with their documents and stories - in a single response across all crypto projects. ## When to use vs `trending_stories_tool` This is a superset of `trending_stories_tool`: same stories, plus trending words, their context and AI-generated bull/bear summaries. It calls an LLM, so it is slower and has a tighter per-tool rate-limit sub-cap than every other tool. If only trending stories are needed, call `trending_stories_tool` instead; set `include_words: false` / `include_stories: false` to drop a half that is not needed. Do not call both tools for the same question. ## Parameters - `time_period` - Time period for trending data (e.g., '1h', '6h', '1d', '7d'). Defaults to '1h' (last hour). - `size` - Number of items per category to return (max 10). Defaults to 10. Only the 2 most recent trend periods are returned, whatever `time_period` is. A period is 1 hour for time_period up to 1d, 6 hours up to 7d, and 1 day beyond that, so e.g. '2d' returns only the last 12 hours. When older periods are dropped, `metadata.notice` says so and `metadata.returned_since` gives the start of the oldest period returned. - `include_stories` - Include trending stories in response. Defaults to true. - `include_words` - Include trending words in response. Defaults to true. ## Response - `trends` - Combined trending data containing stories and words. - `metadata` - Request metadata including time period, size, and included data types. - `errors` - Any non-fatal errors encountered during data fetching. ## Trending Data Structure ### Stories - `title` - Title of the trending story. - `summary` - Summary of the story. - `score` - Trending score. - `query` - Search query used to find the story. - `related_tokens` - List of related crypto tokens (format: "BTC_bitcoin"). - `bullish_sentiment_ratio` - Bullish sentiment ratio. - `bearish_sentiment_ratio` - Bearish sentiment ratio. ### Words - `word` - The trending word. - `score` - Trending score. - `slug` - Associated project slug (if word is project-related). - `summary` - AI-generated summary of discussions. - `bullish_summary` - Summary of bullish sentiment. - `bearish_summary` - Summary of bearish sentiment. - `positive_sentiment_ratio` - Positive sentiment ratio. - `negative_sentiment_ratio` - Negative sentiment ratio. - `neutral_sentiment_ratio` - Neutral sentiment ratio. - `positive_bb_sentiment_ratio` - Positive bull/bear sentiment ratio. - `negative_bb_sentiment_ratio` - Negative bull/bear sentiment ratio. - `neutral_bb_sentiment_ratio` - Neutral bull/bear sentiment ratio. - `context` - Related words that appear with this trending word. - `documents_summary` - AI-generated summary of related social media discussions.

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• related_entriesA

  PersonalKnowHowA

  Given an entry id (from a prior query_knowhow or list_by_type result), returns other entries that share at least one tag or the same content provider -- the only two relationships this corpus currently tracks (there is no 'led to' or 'used in' relationship here, only shared tag/provider). This is NOT a similarity or relevance judgment -- two entries sharing a broad tag (e.g. both tagged 'data-science') can be quite different in substance; read each related entry's own label/type before treating it as meaningful. Each group is capped at 15 entries, sorted by label, with the true total count shown separately so you know if results were truncated -- call list_by_type on that type if you need the full set. Useful for 'what else is connected to X' or 'what did they do that relates to this specific course/certification/endorsement' -- questions query_knowhow's independent similarity search can't reliably answer, since two entries can be genuinely related without their description text reading alike (e.g. a course title and an endorsement phrase for the same skill, worded completely differently).

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• analyze_citation_structure_batchA

  VantageA

  Analyze the structural shape of the winning AI answer across several related keywords/topics in one call: does each lead with a list, how long is the opening, how many sources it cites. It covers a topic cluster in one call, for content planning across related pieces. Read-only: no side effects, safe to retry. Costs 1 quota unit per keyword in the batch (free tier is 30 units/month shared across all the metered tools, so up to 30 keywords total that period if nothing else is used). A per-keyword provider error doesn't fail the whole batch - that keyword's entry just carries an "error" field instead. Returns: {"results" (list, one {"keyword", ...same shape as analyze_citation_structure, or "error"} per keyword, in the order given), "summary": {"topics_analyzed", "topics_requested", "list_led_count", "avg_sources_cited", "avg_community_pct" (average source_mix.community_pct across the analyzed topics)}}. Args: keywords: topics/queries to analyze, e.g. ["how to reduce churn", "churn rate benchmarks", "reduce customer churn saas"]. Max 10. country: market to read the answers in, e.g. "Italy". Defaults to "United States". language: language code, e.g. "it". Defaults to "en". engine: "chat_gpt" (default), "gemini" or "perplexity", as in analyze_citation_structure. One answer per topic.

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• eve_searchA

  Netmon (demo)A

  Search Suricata EVE-format IDS events. Wraps GET /api/eve/list (permission: logs); tag-scoped server-side. Severity is Suricata-native: 1=high, 2=medium, 3=low/info — a 3-point scale, NOT syslog's 0-7. Takes names or ints: 'high'=1, 'medium'=2, 'low'/'info'/'informational'=3. Single value or an array, which may mix the two forms (e.g. ["high", 2]). IP filters: passing only src_ip or only dst_ip matches either side (OR); pass both to AND them together. `device_id` is a convenience — the controller resolves it to the device's IP and matches src_ip OR dst_ip (eve_log has no device_id column). Window: `hours` (1-168, default 24) OR `start_time`+`end_time`. `limit` defaults to 50 (max 500). `total` is the full match count — narrow via severity/IP/signature_id when truncated. Example: eve_search({severity: "high", hours: 2})

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• log_severity_summaryA

  Netmon (demo)A

  Count log events grouped by severity over a time window. One tool, three backends — pass `stream` to pick which. stream='syslog' → wraps /api/syslog/sevSum (severity 0-7, syslog scheme) stream='eventlog' → wraps /api/eventlog/sevSum (severity 0-5, Windows scheme) stream='eve' → wraps /api/eve/sevSum (severity 1-3, Suricata scheme) Use this for triage before pulling rows: 'how many criticals on host X today' returns one tight rollup instead of 1000 sample rows. Every result includes both the numeric key and a `label` so the LLM doesn't have to memorize three different scales. Window: `hours` (1-168, default 24) OR `start_time`+`end_time` (ISO-8601 UTC). Optional `device_id` narrows to one device — for eve, the controller translates this to a src_ip OR dst_ip match automatically (eve_log has no device_id column). ALL-ZERO IS NOT THE SAME AS CLEAN. A dead feed and a quiet network produce byte-identical answers here, so every response carries `meta.stream_health`: active — events landed inside your window; the counts mean what they say. stale — your window is empty, but the stream produced up to `last_event_at`, before it. The feed is alive and the empty window is real. silent — nothing in your window AND nothing in the 168h before it. Never report 'clean' from this state; `note` names the producer to check first. unknown — freshness could not be established. The zeros prove nothing. stale/silent come from re-asking the same stream over a window that strictly contains yours (one extra call, and only when every bucket is zero). No staleness threshold is guessed: `stale` means exactly 'the newest event predates the window you asked for', which on a 1-hour window is unremarkable. `checked_back_hours` and `events_before_window` say how much history the verdict rests on. Permission: logs. Tag-scoped server-side. Example: log_severity_summary({stream: 'syslog', hours: 1, device_id: 42})

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• save_content_exclusionA

  MarkA

  Creates or retires a content exclusion: a literal phrase Mark enforces (block or warn), optionally limited to one channel. BrandProfile (voice.do, voice.dont, voice.principles, doctrine) is prose guidance the model reads. ContentExclusion is phrases Mark enforces. To change an exclusion, retire it and create a new one — exclusions are never edited in place. Pass phrase and severity to create, plus feedbackId when report_feedback recorded the person asking for this rule. Pass id and active: false to retire. Related: get_brand_context, update_brand_profile, report_feedback.

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• calculate_cyprus_unemployment_benefitA

  PoliErgaleioA

  Estimates the Cyprus unemployment benefit using statutory percentage-point dependant additions and a capped earnings-related supplement, and separately assesses entitlement when qualifying facts are supplied. Use to estimate the conditional Cyprus unemployment benefit amount and separately assess entitlement. The basic rate is 60%, plus 20 percentage points for a dependent spouse and 10 percentage points per dependent child or other dependant (up to three); the earnings-related supplement is 50% of supplementary insurance earnings, capped at one weekly basic insurable earning. Require the claim date, relevant-year insurable earnings and dependants to estimate an amount. Ask for qualifying insurance history, employee status, unemployment registration and availability for work before claiming entitlement; when those facts are missing, state that entitlement is undetermined and ask each missing follow-up question. Do not infer those facts from annual earnings.

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• create_uploadA

  AskEditorA

  [write] Open an upload of a local file (video, image or audio, up to 4 GB) and sign a URL for each part. Use for a file on your machine: PUT each part to its url, keep each ETag, then complete_upload. For parts past the first 50, or after 15 minutes, call again with upload_id and part_numbers. Not for a web address (use import_media_from_url). Returns upload_id, part_size, part_count, parts [{part_number, url}], how (a shell recipe) and next_part_numbers when more remain. Related: complete_upload, import_media_from_url, list_media. Full docs: load_skill with tools: [name].

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• set_clip_timingA

  AskEditorA

  [write] Set a clip's start and/or its timeline length directly. It keeps the source in-point (300 ms minimum, capped by the source unless it loops). Use to hold an image or a title longer, or to place a clip at an exact time. Not for changing where in the source it starts (use trim_clip). Returns the changed clips' rows (with handles) and counts. Related: trim_clip, set_clip_speed, ripple_timeline. Full docs: load_skill with tools: [name].

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• search_libraryA

  The Small Business LibraryA

  Search the library for what the Small Business Owners Community has learned about an owner's question. Use this first for any small business question, however it's worded: "raise my prices," "a client won't pay," "can't find good people," "working too many hours," "nobody to talk to about the business." Returns up to 8 short passages, each with a match label (strong, related or weak), the title, date, read link, a watch link when there is one, and an id to pass to get_document.

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• law_bills_get_billA

  UK Business Tools - LedgerhallA

  USE THIS TOOL WHEN you have a bill_id (from bills_search_bills) and want the full detail. Returns sponsors, current stage, long title, summary, and Royal Assent date if enacted. Summary text is capped per max_summary_chars — check summary_truncated in the response. AFTER calling, use parliament_search_hansard(query=bill_short_title) to find the bill's parliamentary debates, or bills_search_bills with a related keyword for adjacent bills.

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• paywall__customer_deduct_from_fupA

  NetfluidC

  Deducts a unit from the customer's available workflow allowance. Do not call this tool when the customer is requesting assistance related to the pay wall and its subscriptions. This tool should be called after each AI response that is not pay wall related. @param customer_id: The customer's database id @return: a json object, containing the customer_id and remaining fup token balance in the "values" object

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• auditA

  mcpA

  Perform comprehensive audit of a website URL. Fetches the URL content ONCE and provides a combined report with: - Classification: category, subcategory, language, sentiment, demographics - SEO Analysis: score, grade, issues, recommendations - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores - AEO Analysis: AI answer engine optimization score, metrics, issues, signals (includes full Citation Readiness analysis in the nested 'citation' key) - Advertiser Matching: best-fit advertising networks with scores - Similar Sites: competitor/related sites from the same category This is more efficient than calling classify_url, analyze_seo, analyze_eeat, analyze_aeo, select_advertiser, and find_similar_sites separately as it only fetches the page once. Args: url: The website URL to audit (e.g., "https://example.com"). Returns: Comprehensive audit report with: - url: The analyzed URL - classification: Category, subcategory, language, sentiment, demographics - seo: Score, grade, issues, recommendations - eeat: EEAT score, grade, category scores, issues, signals - aeo: AEO score, grade, metrics, issues, signals (includes citation results) - advertisers: Matched advertising networks with scores - similar_sites: Related sites from the same category (up to 10) - cached: Whether result was from cache

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