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742,824 tools. Updated 2026-11-04 17:14

"A framework for building server-side applications with NestJS" matching MCP tools:

  • 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" } }
    ConnectorNo auth
  • 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.
    ConnectorNo auth
  • 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. contact.organisation is printed as the document's "Prepared for" heading, so it should be the organisation's name as it should appear on the document rather than a shorthand. Returns the session ID and a status of profile_saved — it does not return the framework, which is retrieved by get_ai_governance_framework. The profile can be re-submitted on the same session: it is overwritten rather than duplicated, the contact record is keyed on the email address, and any framework already generated for that session is discarded. No authentication, and no charge at this step.
    Connector
    Destructive
    No auth
  • Everything needed to go from nothing to a rendered document in one call: the steps to create an API key in the dashboard, and — when you name a `framework` — the install command for the Kamy SDK, the environment variable it reads, and the client-setup snippet for that stack. Add a `template` slug and it also returns a ready-to-paste route handler that renders it. Every argument is optional and each one only adds a section, so calling this with no arguments is the right move when a user has no key yet, and calling it with framework + template is the right move when they are wiring the first endpoint. This replaces the separate install_sdk, generate_integration_code and get_api_key_instructions tools removed in 1.5.0. Pure text: it makes no API call, reads no account state, and needs no API key.
    ConnectorNo auth
  • Everything needed to go from nothing to a rendered document in one call: the steps to create an API key in the dashboard, and — when you name a `framework` — the install command for the Kamy SDK, the environment variable it reads, and the client-setup snippet for that stack. Add a `template` slug and it also returns a ready-to-paste route handler that renders it. Every argument is optional and each one only adds a section, so calling this with no arguments is the right move when a user has no key yet, and calling it with framework + template is the right move when they are wiring the first endpoint. This replaces the separate install_sdk, generate_integration_code and get_api_key_instructions tools removed in 1.5.0. Pure text: it makes no API call, reads no account state, and needs no API key.
    ConnectorNo auth
  • Returns the organization's development standards: coding conventions, project structure, and framework-specific rules. Read-only. Call it before writing or reviewing code, so the result follows this organization's rules rather than general defaults. Call it first without a section to get an index of available sections, each with a note on what it covers, then call again with one section id copied from that index; inventing a section id returns a not-found error naming that step. Request only the sections a task needs - the full content of one section can be long. The framework argument is deprecated: use section with the "framework:" prefix instead. It returns prose rules, not data - use get_style_tokens for visual values and get_component for component APIs.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables Nest applications to expose decorated provider methods as MCP tools, resources, and prompts over Streamable HTTP or stdio, with Nest guards, interceptors, pipes, filters, OAuth 2.1 resource-server support, and an in-memory test client.
    2
    MIT

Matching MCP Connectors

  • Unofficial MCP server for the Ionic Framework documentation, components and blog.

  • Production telemetry for NestJS apps: traces, errors, regressions, jobs and alerts.

  • Seller-side: list unanswered quote requests (status=requested). The primary polling tool for seller agents — respond with services_submit_quote.
    ConnectorNo auth
  • Manual fallback: returns a node type+operation's config SCHEMA (the fields you can set) — NOT a live node's saved config (use get_node for that). Takes "type:operation" pairs (e.g. ["automation-slack:send_message_to_channel"]). Prefer search_operations(detail_level='full') for intent lookup, or update_workflow(include_configs=true) while building.
    ConnectorOAuth
  • Search SaidItHere for real-world software dilemmas, framework gotchas, tool fatigue, and battle-tested community consensus workarounds from Reddit, Hacker News, GitHub, and Stack Overflow. Usage Guidelines: - Primary discovery tool: use FIRST when investigating bugs, library gotchas, unexpected price hikes, or developer complaints by keywords. - Sibling routing: follow up with 'get_problem(slug)' using the discovered dilemma slug to inspect full evidence quotes, sources, and step-by-step workarounds. - Sibling routing: if 0 matching dilemmas are returned, use 'suggest_dilemma' to queue the topic for crawler consensus synthesis. - Do NOT use for generic language syntax lookups or textbook documentation queries. Behavior & Side Effects: - Pure read-only, safe, and idempotent query without side effects. Does not modify user, session, or database state.
    ConnectorNo auth
  • Get a complete, distinctive, reference-backed art direction for a website: palette with exact hex roles, type pairing, layout DNA, hero spec, component treatments, imagery rules, matched motion recipes, and public-product reference evidence. Use FIRST, before building, so the site has a coherent direction instead of defaults. The catalog holds 14 directions: 9 with light base palettes and 5 dark — pass tone to constrain. If you only know the business name, call it anyway: the response will give you a few quick questions to ask the user, then call again with their answers as vibe/audience. REDESIGNS: if the business has an existing website, pass its URL as current_site_url — Standout fetches it server-side and returns a content inventory (services, prices, hours, contacts) plus a redesign protocol, so no questions are needed.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Returns instructions for migrating to PropelAuth in a frontend framework such as React, JavaScript, TypeScript, or when using Next.js for just the frontend (e.g. client-side rendered). Guidance includes migrating from several auth providers, such as Clerk or Auth0. Each guidance will include documentation from the auth provider and PropelAuth. It is important to follow the instructions carefully to ensure a successful integration. Make sure to use the 'Installation' guidance first. It is important to call every guidance to ensure a successful integration. Do not update a component/hook/etc from the auth provider until you receive guidance about that component/hook/etc. CRITICAL: If the current implementation uses a traditional OAuth/OIDC flow (e.g., via express-openid-connect, passport-auth0, or similar backend-managed session libraries), you MUST select 'OAuth' as the framework, regardless of the frontend library (React/Vue/etc.). Only select 'React' or 'Javascript' if the current implementation uses a frontend-only SDK (like @auth0/auth0-react) or if using fullstack Next.js.
    ConnectorNo auth
  • 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 }
    ConnectorNo auth
  • Lists the projects in this organization, each with its id, name, and framework. Read-only, takes no arguments, and returns only the projects the calling credential may see. Call it first in a session: the returned id is the project_id that every other tool in this server requires, and guessing that id fails. It does not return components, packages, or tokens - use list_components, list_packages, or get_style_tokens for those.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • Public mode returns FS AI RMF framework reference data only — not org-specific scoring. Use when assessing an organization FS AI RMF governance maturity stage or preparing a regulatory AI roadmap presentation. Returns INITIAL, MINIMAL, EVOLVING, or EMBEDDED classification with stage criteria and remediation priorities. Example: EVOLVING stage organizations have documented AI policies but lack systematic model validation — typical gap to EMBEDDED is 18-24 months and 12-15 additional controls. Connect org MCP for org-specific scoring. Source: FS AI Risk Management Framework. $0.02 USDC per call.
    ConnectorNo auth
  • How this Aevia connection works, plus playbooks for results, reports, systems. Returns a skill's playbook as the result; takes no action itself. A playbook is step-by-step guidance for a multi-step job, too long for a description. `connector_guide` covers how this connection works: workspaces, refs, finding data, the library, building, calculating and failures. `assessment_interpretation` covers reading and comparing results: what an indicator result is and is not, a figure's anchors, functional-unit equivalence and comparison discipline. `report_writing` covers writing results up as a document, from a screening note to an ISO 14044 study. `product_system_authoring` covers building a new product system with `lca_compose_assembly` / `lca_compose_linked`: build order, which of the two fits, failure modes, and tagging life-cycle phases. A loaded playbook stays in context; one load per session suffices. Skills are gated on what the token can call; an unavailable request returns the available list.
    ConnectorAPI key