"Learning NestJS Framework Knowledge" matching MCP tools:

• generate_framework_analysis

  jeda-ai

  Runs a specific framework against a user's inputs and produces a full analysis: prose explanation + structured fields + a self-contained SVG visualisation. Powered by the Jeda.ai · Visual AI framework knowledge graph. ALWAYS call `recommend_framework` FIRST to obtain a valid framework_id -- it returns the exact namespaced slug to pass here. Framework ids are namespaced by category (e.g. SWOT = "cms_swot-analysis", Porter's 5 Forces = "cms_porters-five-forces"); a bare slug like "swot-analysis" will 404. REQUIRED post-processing on success: the response's first text block contains a `curl -fsSL` save-directive for the SVG. Save the file locally and surface it as a file chip — do NOT summarise the visual in prose. Input: framework_id (namespaced slug from `recommend_framework`) + user_inputs object (per-framework field set), OR a free-text `raw_prompt` fallback. Example: { "framework_id": "cms_swot-analysis", "user_inputs": { "subject": "Q3 EU market entry", "context": "B2B SaaS, $5M ARR, US-headquartered" } }

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• list_investment_theses

  crashtestyourstrategy

  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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• recommend_framework

  jeda-ai

  Recommends business / strategy / risk frameworks for a stated problem. Powered by the Jeda.ai · Visual AI framework knowledge graph (~2,100 frameworks across 19 categories, edge-curated). Use when the user describes a business problem ("customer churn rising", "evaluating market entry", "need to assess vendor risk") rather than naming a specific framework. Returns top-N frameworks ranked by fit, each with a concrete reason citing the specific problem signals matched. Input: just the problem statement is enough. Optional faceted filters (`persona`, `regulation`, `decision_stage`) narrow the candidate set. Set `limit` between 3 and 10 for picker UIs. Pair with `generate_framework_analysis` to actually run a recommended framework against the user's inputs. Example: { "problem_statement": "We need to decide whether to enter the EU SMB market in Q3", "decision_stage": "decide", "limit": 5 }

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• submit_ai_governance_profile

  australian-ai-governance-framework

  Submits the organisation profile and contact details for an Australian AI governance framework. The profile determines which legislation the framework identifies, so the answers should reflect the organisation's actual circumstances — turnover in particular, since the Privacy Act's small business threshold sits at $3 million and several categories are caught regardless of turnover. Takes the session ID from start_australian_ai_governance_framework together with the questionnaire answers. Writes the profile against the session and stores the supplied name, email and organisation as a contact record. Returns the session ID and a status of profile_saved — it does not return the framework. Call get_ai_governance_framework next to retrieve it. Safe to call again on the same session: the profile is overwritten rather than duplicated, and the contact record is keyed on the email address. Re-submitting does discard any framework already generated for that session, so call it again only to correct an answer. No authentication, and no charge at this step.

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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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• lorg_search

  lorg-mcp-server

  Search the Lorg knowledge archive. Use this to find existing contributions before submitting (to avoid duplicates) or to discover useful knowledge from other agents. Searches PUBLISHED contributions only; for the raw event/audit log use lorg_archive_query.

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• query_dataset

  tw-market-data

  Query rows with built-in look-ahead protection. ★ POINT-IN-TIME: pass `as_of` (YYYY-MM-DD) for backtesting/agent-learning. For non-point-in-time-safe datasets (fundamentals, monthly_revenue, dividend_policy…) rows are filtered by DISCLOSURE date <= as_of, so the agent only sees what was public at that moment. Omit as_of only for present-day lookups (warned). Args: dataset_id: see list_datasets. tickers: e.g. ['2330','2317']. start/end: 'YYYY-MM-DD' range. as_of: knowledge-time cutoff 'YYYY-MM-DD' (use for backtests). limit: <=5000. Returns: {meta:{table,coverage,row_count,as_of_applied,point_in_time_safe,warnings}, data:[...]} Example: query_dataset('fundamental_income', tickers=['2330'], as_of='2023-06-30')

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• get_interpretation

  corpus

  Return the Wheel of Heaven interpretive framework's reading of a topic — explicitly the project's own Raëlian-canon-centred position, NOT mainstream consensus. Accepts a framework topic (overview, hypothesis, terminology, timeline, sources, method) for the curated narrative documents, or any other term to get the framework reading from the closest wiki entry. Use fact-layer tools (get_passage, compare_traditions) for source-grounded data without this framing.

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• get_outfit_preset

  Heista

  Get one outfits preset by id, including its full body payload (framework, agent config, etc.). Call the matching list tool first to discover ids. Free, read-only.

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• list_suites

  saferagenticai-mcp

  List all 16 suites in the SaferAgenticAI framework (9 drivers + 7 inhibitors) with subgoal counts and titles. Call this first to orient.

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• get_project_context

  main

  Captures the user's project architecture to inform i18n implementation strategy. ## When to Use **Called during i18n_checklist Step 1.** The checklist tool will tell you when to call this. If you're implementing i18n: 1. Call i18n_checklist(step_number=1, done=false) FIRST 2. The checklist will instruct you to call THIS tool 3. Then use the results for subsequent steps Do NOT call this before calling the checklist tool ## Why This Matters Frameworks handle i18n through completely different mechanisms. The same outcome (locale-aware routing) requires different code for Next.js vs TanStack Start vs React Router. Without accurate detection, you'll implement patterns that don't work. ## How to Use 1. Examine the user's project files (package.json, directories, config files) 2. Identify framework markers and version 3. Construct a detectionResults object matching the schema 4. Call this tool with your findings 5. Store the returned framework identifier for get_framework_docs calls The schema requires: - framework: Exact variant (nextjs-app-router, nextjs-pages-router, tanstack-start, react-router) - majorVersion: Specific version number (13-16 for Next.js, 1 for TanStack Start, 7 for React Router) - sourceDirectory, hasTypeScript, packageManager - Any detected locale configuration - Any detected i18n library (currently only react-intl supported) ## What You Get Returns the framework identifier needed for documentation fetching. The 'framework' field in the response is the exact string you'll use with get_framework_docs.

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• get_validation_framework

  Demand Discovery AI

  Returns the full three-step Demand Discovery validation framework: (1) Market Research, (2) Demand Discovery Report with the Demand Score and Build/Pivot/Kill verdict, (3) Agentic Launch (90-day continuous outreach). Use when a user asks "how do I validate an idea?", "what's the methodology?", or wants to understand the structured approach. Built on the "behavior over opinion" principle. Trigger phrases: "what's the framework", "demand discovery framework", "what's the methodology", "how does demand discovery work", "step by step validation", "what's the process", "how to structure validation", "validation framework", "validation methodology", "structured validation", "show me the framework", "explain the methodology".

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• compliance.regulatory_calendar

  DPX — Institutional Cross-Border Settlement

  Returns a structured calendar of upcoming and in-effect compliance obligations across MiCA (EU crypto-asset markets regulation), SFDR (Sustainable Finance Disclosure Regulation), CSRD (Corporate Sustainability Reporting Directive), the US GENIUS Act (payment stablecoin framework), and FATF Recommendations 15/16. For each event: framework, jurisdiction, requirement summary, effective date, impact level, and article reference. Also returns a DPX alignment section mapping each framework to the specific DPX endpoints that satisfy it. Use this before settlement workflow design, compliance gap analysis, or regulatory reporting.

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• coldstate_domains

  ColdState Knowledge Search

  List all available knowledge domains in ColdState's global knowledge base with entry counts.

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• get_now

  Cameron Rye Portfolio MCP Server

  Return what Cameron is currently working on, learning, building, reading, and up to in life — the live /now page sections.

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• explain_concept

  ReliaSim

  Definitional primer for ReliaSim's framework concepts — Constraint, Buffer, Interrupt, Converter, cascading losses, OEE, Gain/Loss methodology, Buffer Tradeoff. Returns bundled theory content, NOT interpretation of any specific simulation run. Use for 'what is X?' / 'how does X work?' / 'explain the framework' questions. For line-specific claims (throughput, availability, what-if), call the sim tools instead.

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• get_knowledge_stats

  mcp-klever-vm

  Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.

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• get_my_briefing

  welcome

  Your daily briefing at The Balanced Investor Club — a read on your own activity: morning brief, journal counts, the instruments you follow, mood highlights, activity, and your learning journey. A mirror, never advice.

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• get_framework_docs

  main

  Retrieves authoritative documentation directly from the framework's official repository. ## When to Use **Called during i18n_checklist Steps 1-13.** The checklist tool coordinates when you need framework documentation. Each step will tell you if you need to fetch docs and which sections to read. If you're implementing i18n: Let the checklist guide you. Don't call this independently ## Why This Matters Your training data is a snapshot. Framework APIs evolve. The fetched documentation reflects the current state of the framework the user is actually running. Following official docs ensures you're working with the framework, not against it. ## How to Use **Two-Phase Workflow:** 1. **Discovery** - Call with action="index" to see available sections 2. **Reading** - Call with action="read" and section_id to get full content **Parameters:** - framework: Use the exact value from get_project_context output - version: Use "latest" unless you need version-specific docs - action: "index" or "read" - section_id: Required for action="read", format "fileIndex:headingIndex" (from index) **Example Flow:** ``` // See what's available get_framework_docs(framework="nextjs-app-router", action="index") // Read specific section get_framework_docs(framework="nextjs-app-router", action="read", section_id="0:2") ``` ## What You Get - **Index**: Table of contents with section IDs - **Read**: Full section with explanations and code examples Use these patterns directly in your implementation.

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• search_arxiv

  Developer Tools MCP Server

  Search arXiv for academic papers in computer science, machine learning, AI, physics, and mathematics. Returns paper titles, authors, abstracts, submission dates, and direct PDF download links. Use for researching algorithms, ML techniques, or emerging CS topics.

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