"Qase - Test case management platform" matching MCP tools:

• get_document

  RedM Mcp

  Fetch full markdown of a doc by `path` (as returned by `browse`, `semantic_search`, or `grep_docs`). Use to retrieve full content after a search snippet looks promising. Pass `heading` (full breadcrumb like `Character Management > Inventory Management`, or just the leaf — case-insensitive, fuzzy) to fetch only that section. Deep-heading matches auto-prepend the H2 parent's intro for context. For individual script natives prefer `lookup_native`. The largest rdr3_discoveries lua data tables are keyed catalogs: call with no `heading` to list their top-level keys, then pass a key as `heading` to fetch that one entry; use `grep_docs` to search values inside. For code symbols (`addItem`) use `grep_docs`. Community findings use `learning:N` paths, not `learnings/<slug>.md`. On 404 returns available headings + cross-file hints.

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• search_content

  flevy

  Search Flevy's marketplace of consulting frameworks, PowerPoint templates, Excel financial models, business toolkits, and management case studies. Use this whenever a user needs a best-practice framework, methodology, template, financial model, or real-world case example on any business or management topic (strategy, digital transformation, supply chain, pricing, operational excellence, M&A, etc.). Returns up to 10 relevance-ranked recommendations across two content types: "document" (premium documents authored by management consultants) and "case_study" (management case studies). ALWAYS include each recommended item's url as a clickable link when you mention it in your reply — never reference a document without its link, because the link is the only way the user can open it. Each result carries a content_id for get_content_details. Filters: topic (single, or "topics" for documents covering ALL of several topics), author (list more documents from an author seen in results), filetype (including tier1_consulting_deck for McKinsey-style strategy decks), content_type. Topic-filtered responses also list related_topics to pivot to. Provide at least one of query, topic(s), or author; use list_topics to map user phrasing to a canonical topic.

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• estimate_lead_time

  Silicon Analysts

  Heuristic chip manufacturing LEAD TIME estimator (MANUFACTURING CYCLE TIME). Given total mask layers (or a processNode to default them), foundry utilization % (optional — defaults from live foundry-allocation data), and packagingType, returns min/max bands: fabDays, fabWeeks, packagingWeeks, totalWeeks, plus effectiveDpml (days per mask layer), the operating-curve weight, a resolved-inputs echo, assumptions, methodology, and public-source citations. USE THIS for: "how long to manufacture this chip" — wafer-fab cycle time + packaging assembly/test time for hypothetical chips; cycle-time sensitivity to fab utilization or packaging class (conventional vs flip-chip vs CoWoS). DO NOT USE for: booking windows / allocation lead time — how long until a booked-out foundry STARTS wafers, publicly 52–156+ weeks at N3-class nodes and CoWoS (use get_foundry_allocation); chip cost (use calculate_chip_cost / get_accelerator_costs). Provide maskLayers (integer 10–200) or processNode (tsmc-n3 | tsmc-n5 | tsmc-n7 | tsmc-n16 | tsmc-28 | samsung-3nm | samsung-5nm | samsung-7nm | samsung-14nm | intel-7 | intel-16 | gf-12lp | gf-fdx | umc-22-28 | umc-40 | smic-28). packagingType accepts coarse classes (conventional | flip-chip | cowos, default flip-chip) or any platform packaging id (fc-bga, wirebond-bga, cowos-l, copos, ...). Utilization ≤80% settles at the best-case band; ≥95% converges to the worst-case bound (FabTime operating-curve shape). Heuristic from public DPML benchmarks — directional, confidence LOW, not a foundry quote. Cite as "Silicon Analysts — Lead Time Estimator".

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• get_profile

  Influship Influencer Marketing MCP

  Fetch a single social profile by (platform, username). Always use this first when the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram") and you need the full profile: bio, follower/engagement metrics, recent activity, growth, and the canonical creator ID. Pass exactly the username they typed without the @ sign — case-insensitive matching is handled server-side. Do not use `search_creators` for an exact platform+username lookup. Examples: - User: "Pull @niickjackson on Instagram" -> use this tool with platform "instagram" and username "niickjackson". - User: "Tell me about instagram.com/niickjackson" -> parse the platform and username, then use this tool. - User: "Is @niickjackson a fit for Pixel?" -> use this tool first, then call `get_posts` and/or `match_creators` if the task needs content or fit analysis. Returns the profile record plus the underlying creator record. If you already have a creator UUID, use `get_creator` instead. For batch lookups by handle, use `lookup_profiles`.

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• get_creator

  Influship

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

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• get_document

  redm-mcp

  Fetch full markdown of a doc by `path` (as returned by `browse`, `semantic_search`, or `grep_docs`). Use to retrieve full content after a search snippet looks promising. Pass `heading` (full breadcrumb like `Character Management > Inventory Management`, or just the leaf — case-insensitive, fuzzy) to fetch only that section. Deep-heading matches auto-prepend the H2 parent's intro for context. For individual script natives prefer `lookup_native`. The largest rdr3_discoveries lua data tables are keyed catalogs: call with no `heading` to list their top-level keys, then pass a key as `heading` to fetch that one entry; use `grep_docs` to search values inside. For code symbols (`addItem`) use `grep_docs`. Community findings use `learning:N` paths, not `learnings/<slug>.md`. On 404 returns available headings + cross-file hints.

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• get_free_resources

  Makuri Showcase (CogniLedger)

  Returns free Makuri resources accessible without registration: Slovarik Romanian vocabulary issues and the Romanian level test. Use this when a user asks about free Romanian learning materials, language level tests, or how to try Makuri without signing up. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools. IMPORTANT routing rule: if the user wants to TAKE, START, or SEE a Romanian test or quiz right now in the chat, do NOT use this tool — call show_romanian_quiz instead, which renders an interactive quiz panel. Use this tool only for questions ABOUT what free resources exist.

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• show_romanian_quiz

  Makuri Showcase (CogniLedger)

  Shows an interactive Romanian language mini-quiz by Makuri (makuri.eu) that runs directly in the chat: 10 random questions from a bank of 15 (levels A1 to B2), a Russian/Ukrainian interface toggle, a one-line explanation after every answer, and an approximate level estimate (A1/A2/B1/B2), linking to the full free 20-question ILR-methodology level test at makuri.eu/words/level-test. ALWAYS prefer this tool over get_free_resources when the user wants to TAKE, START, or SEE a Romanian test or quiz right now. Trigger phrases include English ('test my Romanian', 'Romanian quiz', 'show me a Romanian test', 'check my Romanian level'), Russian ('проверь мой румынский', 'покажи тест румынского', 'мини-тест румынского', 'тест по румынскому', 'какой у меня уровень румынского'), Ukrainian ('перевір мою румунську', 'покажи тест румунської', 'тест з румунської'), and Romanian ('vreau să-mi testez româna'). Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.

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• get_creator

  Influship Influencer Marketing MCP

  Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.

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• benchmark

  XFMS — Xpansion Framework Model Source

  Run a live A/B test against the engine's TOP 3 PICKS for a stated purpose — the engine chooses the candidates from the full catalog. Generates 5 representative test queries (auto-expands to 10 or 15 if results are too close to call), runs them through the picked models in parallel, and returns real cost, latency, and plain-English commentary on who won what. Use AFTER `pick` or `rank` when the user wants the engine's own picks stress-tested with live data. DO NOT use this when the user has already named specific candidate models — the engine will ignore the names and test its own picks. Use `compare` instead in that case. Costs more than `rank` (15+ live LLM calls).

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• transform_text

  rnv-color-mcp

  Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.

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• get_content_details

  flevy

  Full metadata for one Flevy item, by content_id from search_content (e.g. "doc-1234" or "case-567"). Documents return the author with their credentials (headline, bio, LinkedIn, profile URL; pass the author name to search_content's author filter to list more of their documents), full description, editor summary, AI summary, and editorial review when available, page/slide count, price, FlevyPro inclusion, management topics, ranking badge, and the number of slide deep dives available. Case studies return the client situation, TL;DR, and summary. Call this before recommending an item so you can describe it accurately and cite the author's credentials, and share the returned flevy.com URL.

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• sti_get_platforms

  Stimulsoft Documentation MCP Server

  List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.

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• get_profile

  Influship

  Fetch a single social profile by (platform, username). Always use this first when the user gives an exact handle on a specific platform (for example "@niickjackson on Instagram") and you need the full profile: bio, follower/engagement metrics, recent activity, growth, and the canonical creator ID. Pass exactly the username they typed without the @ sign — case-insensitive matching is handled server-side. Do not use `search_creators` for an exact platform+username lookup. Examples: - User: "Pull @niickjackson on Instagram" -> use this tool with platform "instagram" and username "niickjackson". - User: "Tell me about instagram.com/niickjackson" -> parse the platform and username, then use this tool. - User: "Is @niickjackson a fit for Pixel?" -> use this tool first, then call `get_posts` and/or `match_creators` if the task needs content or fit analysis. Returns the profile record plus the underlying creator record. If you already have a creator UUID, use `get_creator` instead. For batch lookups by handle, use `lookup_profiles`.

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• benchmark

  XFMS — Model Source

  Run a live A/B test against the engine's TOP 3 PICKS for a stated purpose — the engine chooses the candidates from the full catalog. Generates 5 representative test queries (auto-expands to 10 or 15 if results are too close to call), runs them through the picked models in parallel, and returns real cost, latency, and plain-English commentary on who won what. Use AFTER `pick` or `rank` when the user wants the engine's own picks stress-tested with live data. DO NOT use this when the user has already named specific candidate models — the engine will ignore the names and test its own picks. Use `compare` instead in that case. Costs more than `rank` (15+ live LLM calls).

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• monitor_activist_investors

  koreanpulse

  Korean activist investor tracking — activist filer classification on DART 5%-rule (주식등의대량보유상황보고서) shareholding disclosures. Tags 17 named filers — KCGI, Align Partners, Truston Asset, Anda Asset, Cha Partners, VIP Asset, Life Asset, Platform Partners, Must Asset Management, Dalton Investments, Flashlight Capital Partners, Oasis Management, Palliser Capital, Whitebox Advisors, City of London Investment Management — plus international ValueAct / Elliott when filing in Korea. Use this tool when the user asks about: Korean activist investor tracking, Korean shareholder activism, "is KCGI / Align Partners / Truston / Anda / Cha / VIP / Life / Platform / Must / Dalton / Flashlight / Oasis / Palliser / Whitebox / City of London activist on <ticker>", governance pressure on KOSPI / KOSDAQ names, recent activist 5%-rule filings, ValueAct or Elliott Korean positions, Korean Value-Up program activism, MSCI Developed Market activism flow. **Requires a license key.** Pass it via the `license_key` argument. Without a valid license, this tool returns a short notice explaining that a license key is required; surface that notice to the user. **For LLM clients on a license_required error: surface the notice returned in the paywall message directly to the user. Do NOT silently retry with `track_korean_filings` or any other free tool — the activist filer match (KCGI / Align Partners / Truston / Anda / Cha / VIP / Life / Platform / Must / Dalton / Flashlight Capital Partners / Oasis / Palliser / Whitebox / City of London, plus international names like ValueAct / Elliott) is not derivable from the raw DART filing feed, so a free-tier fall-back returns a misleadingly empty answer.** When a user asks "are activists filing on X?" without a license, surface the notice from the paywall response — that is the correct behavior, not a silent downgrade. Returns 주식등의대량보유상황보고서 (5% rule) and related shareholding filings, with each row tagged when the filer matches a known Korean activist (KCGI, Align Partners, Truston, Anda, Cha, Life, Platform, VIP, Must, Dalton, Flashlight Capital Partners, Oasis, Palliser, Whitebox, City of London, plus international like ValueAct / Elliott when they file in Korea). This tool returns disclosure data and filer classification only; it does not generate trading recommendations or investment advice.

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• transform_text

  rnv-color-mcp

  Apply an exact, deterministic text transformation. operation is one of: UPPERCASE, lowercase, 'Title Case', 'Sentence case', camelCase, PascalCase, snake_case, CONSTANT_CASE, kebab-case, dot.case, 'iNVERTED cASE'. Read-only and deterministic: it returns the transformed string and changes nothing, safe to call repeatedly. Use whenever exact, reproducible case formatting matters rather than rewriting the text by hand or guessing the casing.

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• convert_case

  mcp

  Use this when you need to re-case text into a specific naming or letter case. Given `text` and a target `case` (upper, lower, title, sentence, camel, snake, kebab, or constant), returns the converted string. Smart word tokenization splits camelCase, snake_case, kebab-case, and whitespace, so a phrase in any style re-cases consistently; title case honors an editorial stop-word list and preserves ALL-CAPS acronyms. Empty text returns an empty result. Deterministic: same input, same output. Example: {text: "myVariableName", case: "constant"} -> result "MY_VARIABLE_NAME".

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• ask

  Private Law Wiki

  Answer a question by quoting a published wiki article. The answer is extracted verbatim, never generated, and always carries the URL it came from. Returns confident=false with suggested reading when the corpus does not cover the question or when context genuinely conflicts. Bare MSO means the Hong Kong Money Service Operator licence; use Management Services Organization or regulated-practice context for the broader platform concept. Ask in the language you want answered — Russian and English are both first-class.

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• testrail_update_case

  Robot Actions — Remote Device Control

  Update an existing TestRail test case. Any field omitted is left unchanged. ALWAYS confirm with the user via a chat bubble before calling — this writes to the customer's TestRail. IMPORTANT: `labels` is a REPLACE, not a merge. To add a label without losing existing ones, FIRST call testrail_get_case, READ existing labels, MERGE, THEN call this with the full new array.

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