"Information or resources related to 'Prompt'" matching MCP tools:

• get_contextA

  Vilix AIA

  Load the last few recent messages and semantically related past turns. Call this before you compose your reply. Pass the user's latest prompt only. Vilix runs relevance retrieval internally. For anything more specific you may also call the optional search_semantic / search_keyword / recent_messages tools (e.g. when the user names a source like ChatGPT). Every retrieved item carries an ISO timestamp — when two items disagree about a changing fact (a plan, a status, a decision), the NEWEST timestamp is the latest known value. Related turns may include `context_before`/`context_after` (the adjacent turns) and the payload may include `also_related`: additional nearby matches as compact snippets, newest first — check it before concluding a fact is unknown or unchanged. `chat_id` — pass null (or omit) on a brand-new conversation to also receive `user_rules`, `system_behavior`, `active_projects`, and `active_project_state`. Pass the chat_id returned by a prior `save_turn` to skip those — they are already in the chat's own context from turn 1 and re-injecting wastes tokens. `recent_messages` and `related_conversations` are always returned (they're the cross-tool memory bridge). `attachment_context` (optional, default "") — if the user's CURRENT message has an attachment (file, image, code paste, screenshot OCR), pass a short plain-text summary of it here so retrieval can match on the attachment topic in addition to the bare prompt. Pass the SAME summary to `save_turn` for this turn. Empty = no attachment, ignored.

  ConnectorOAuth

• example_promptsA

  PlanExeA

  Call this first. Returns example prompts that define what a good prompt looks like. Do NOT call plan_create yet. Optional before plan_create: call model_profiles to choose model_profile. Next is a non-tool step: formulate a detailed prompt (typically ~300-800 words; use examples as a baseline, similar structure) and get user approval. Good prompt shape: objective, scope, constraints, timeline, stakeholders, budget/resources, and success criteria. Write the prompt as flowing prose, not structured markdown with headers or bullet lists. Weave technical specs, constraints, and targets naturally into sentences. Include banned words/approaches and governance preferences inline. The examples demonstrate this prose style — match their tone and density. Then call plan_create. PlanExe is not for tiny one-shot outputs like a 5-point checklist; and it does not support selecting only some internal pipeline steps.

  ConnectorNo auth

• well_get_entityA

  WellA

  Read ONE entity with its sub-resources nested in a single call. Convenience over well_get_schema + well_query_records: resolves the field paths for you and returns the single record with its related data expanded. depth (relation-nesting BOUNDARY, 1-3, default 1): 1 = the entity + its direct sub-resources (emails, phones, locations, …) 2 = + the sub-resources' related scalars 3 = the full level-3 graph (LARGER payload — use when you need the whole picture) Stops at depth 3. Aggregates are excluded. Each child collection is capped at 50 rows; for a full list or to page a large child collection, use well_query_records on that child root instead.

  ConnectorNo auth

• get_tier1_recommendationsA

  Tier1 IT AssessmentA

  Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.

  ConnectorNo auth

• edit_videoA

  mcpA

  Edit an existing video from a prompt, or transfer motion onto a subject image. Pass the source in video_url and the change in prompt. Defaults to Google Gemini Omni video edit; switch with model ('kling-edit', 'wan-edit', or 'motion-control' for Kling motion transfer with a subject image in image_urls). This is for changing an existing clip — to make a new video from scratch use generate_video, to extend one use extend_video, to upscale use upscale_media. Returns the video URL.

  Connector

  Destructive

  No auth

• update_promptA

  branchlyA

  Activate or deactivate a prompt by its ID. Use is_active=true to restore a previous prompt version — the currently active prompt of the same type and subtype is deactivated automatically. To change prompt text, use create_prompt instead.

  ConnectorNo auth

• familia_batch_writeA

  FamiliaA

  Use this when the user explicitly asks to create or modify multiple Familia tasks, list tasks, plans, or task attachments in one request, or when one prompt contains multiple standalone dated actions that should become separate tasks. When the same task or plan repeats, use repeatRule/rrule on one operation instead of creating duplicate one-time operations. For a main event/trip plus clearly related dated actions, prefer one create_plan operation with relatedTasks. Internally this runs bounded individual write operations one by one; it does not create a backend transaction.

  Connector

  Destructive

  No auth

• particle_podcast_list_relatedA

  particle-proA

  List the shows most related to a podcast, best first — "shows like this show". Each result carries the related show's slug, a calibrated score in (0,1], and a coarse band (strong: same beat and audience; moderate: overlapping subject or audience; weak: a loose connection) to branch on. Add `include: ["basis"]` to see WHY each pair is related: content similarity of recent episodes, shared topics, shared guests (named), same publisher, shared sponsors — use it to explain a recommendation or to keep only pairs related for the reason you care about (shared guests for booking, content for media planning). Related sets are precomputed per show from its transcripts, topic profile, guest roster, network and advertisers, restricted to the show's language; a show whose set has not been computed yet returns an empty list, not an error. Not a topic browser: for shows that COVER a topic use `particle_podcast_resolve` with `topic_slug`. Not a guest lookup: for where a person has appeared use `particle_podcast_get_guest`. Not advertiser co-occurrence: use `particle_podcast_get_sponsors`. Every related show's slug feeds `particle_podcast_resolve`, `particle_podcast_list_episodes` and the other podcast tools; person slugs in the basis feed `particle_podcast_get_guest`, topic slugs feed `particle_podcast_resolve`'s `topic_slug`. For the five most related shows inline on a resolve, pass `include: ["related"]` to `particle_podcast_resolve` instead of calling this tool.

  ConnectorOAuth

• generate_mediaA

  CluesoA

  Generate an AI image or canvas-code-based animation directly into a clip. - kind="image": text-to-image. Pass `prompt`. Optional: `style_id` (from find type='image_gen_style_packs'), `reference_image_url` or `mcp_upload_id` for image-to-image grounding. - kind="animation": canvas-code animation rendered from a prompt. Pass `prompt`. Optional: `voiceover_text` (drives timing), `base_component_id` (reuse a saved animation as the starting point), `reference_image_url` or `mcp_upload_id` for visual grounding. Generation is asynchronous: the element is created immediately with a stable `element_id` and rendered in the background. Poll `get_clip` (the phantom flag drops once rendering completes). Tip: use this tool whenever the user asks for a "generated", "AI", or "create me a" visual. For uploaded photos / logos / icons / GIFs, use `add_elements` with `element_type='image'` and a `src` or `mcp_upload_id` instead.

  ConnectorNo auth

• 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.

  ConnectorNo auth

• video_to_audioA

  Media Generator — Images, Videos & AudiosA

  Input: A muted video URL along with a textual prompt describing the desired audio. Output: We will return the video URL with the applied audio. Functionality: This tool now takes a muted video and a text prompt as input. It generates an audio track based on the provided prompt and applies this audio to the video, resulting in a video with integrated sound. Steps: 1. We will get the user_id from the request context. 2. We will validate the user's generation tokens. 3. We will call the Audio Application API with the muted video URL and the provided prompt. 4. The API will generate the audio from the prompt and merge it with the muted video, returning a JSON response with the updated video URL. 5. We will return the updated video URL to the user. INSTRUCTION FOR CLIENT MODEL: - Extract the required input parameters 'video_url' (type: string, URL) and 'prompt' (type: string, describing the desired audio) from the user's prompt. - Ignore any extraneous information in the user's input. - Pass the extracted values to this tool as 'video_url' and 'prompt'. - Example: For user input "Add dramatic orchestral music to this video https://example.com/video.mp4", extract 'video_url' as 'https://example.com/video.mp4' and 'prompt' as 'dramatic orchestral music'.

  ConnectorOAuth

• update_promptA

  branchlyA

  Activate or deactivate a prompt by its ID. Use is_active=true to restore a previous prompt version — the currently active prompt of the same type and subtype is deactivated automatically. To change prompt text, use create_prompt instead.

  ConnectorNo auth

• enrich_course_waypointsA

  CourseProfilerA

  Add structured aid stations, checkpoints, cutoffs, and canonical resources to a CRSProf artifact that lacks them. Before enriching, inspect whether the imported source already contains GPX/CRSProf waypoints; if it already contains GPX/CRSProf waypoints, avoid duplicate Start/Finish/aid stations and prefer merging/updating resources, cutoffs, notes, or links on existing waypoint metadata. Prefer waypoints.mode=structured; put non-canonical/free-text aid details in notes/source text because unsupported resource strings are ignored with warnings. Route-only plans should be labeled incomplete unless the CRSProf already includes official waypoints/resources/cutoffs or the user explicitly accepts missing aid/resource details.

  ConnectorNo auth

• search_my_libraryA

  switchA

  Search your library by prompt substring (metadata only — id, prompt, date). Optional folderId scopes to one folder. Only your own assets are returned. This does NOT display images; to show/display results to the user, pass their ids to show_media.

  ConnectorNo auth

• dataset_detailsA

  Datagov IlA

  Full dataset record by id or slug (CKAN package_show), including its resources. Read each resource's "id" (resource_id) and "datastore_active" flag to know which can be queried row-by-row via datastore_query.

  ConnectorNo auth

• score_promptA

  pqs-mcp-serverA

  Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

  ConnectorNo auth

• score_promptA

  PQS - Prompt Quality ScoreA

  Score a prompt's quality across 8 dimensions BEFORE sending it to an expensive model. Returns a 0-80 score, an A-F grade, the per-dimension breakdown (clarity, specificity, context, constraints, output_format, role_definition, examples, cot_structure), and the weakest dimension. USE WHEN: - The user is workshopping a prompt and asks "is this good?" / "will this work?" / "should I add more detail?" - The user is about to send a long or expensive prompt to GPT-4, Claude Opus, or any frontier model, especially in a batch or automation context where rework is costly. - The user mentions iterating on a prompt that produced poor output and wants to diagnose what's missing. - The user pastes a prompt and asks for feedback on it. DO NOT USE WHEN: - The user is asking you to write a prompt for them (write it yourself first, then optionally call score_prompt to verify). - The prompt is conversational chat (this scores task-shaped prompts). COST: Free, no API key required. Rate-limited per IP: 5/min, 10/day, 100/month. If the user exceeds the limit, the response will include a structured upgrade path with subscribe and account URLs. LATENCY: ~2 seconds.

  ConnectorNo auth

• extractA

  SofyaA

  Fetch a webpage and extract specific information using AI. Use this when you need structured data from a page (e.g. pricing, specs, contact info) rather than the raw content. Costs 10 credits. If the page has no usable text (empty or JavaScript-rendered body), the model is NOT called: content comes back empty and usage.low_content is true, rather than a fabricated answer. Gate on usage.low_content (or usage.content_chars) to detect pages you cannot ground on. Returns: content (the extracted text), url, credits_used, credits_remaining, usage (input_tokens, output_tokens, content_chars, low_content). Args: url: The URL to extract from prompt: What information to extract (e.g. "list all pricing tiers with features" or "extract the author name and publication date")

  ConnectorNo auth

• delete_projectA

  CatchAll (by NewsCatcher)A

  Delete a project. By default the project's resources (jobs, monitors, etc.) are detached but kept. Set `delete_resources=true` to also delete the contained jobs, monitors, datasets, and monitor groups. Webhooks are the exception: they are never deleted by this operation — an attached webhook is only detached from the project and keeps working (it may belong to other projects or resources independently of this one).

  ConnectorNo auth

• delete_projectA

  CatchAllA

  Delete a project. By default the project's resources (jobs, monitors, etc.) are detached but kept. Set `delete_resources=true` to also delete the contained jobs, monitors, datasets, and monitor groups. Webhooks are the exception: they are never deleted by this operation — an attached webhook is only detached from the project and keeps working (it may belong to other projects or resources independently of this one).

  ConnectorNo auth

• get_timeline_by_idA

  newtqniaA

  Returns one published timeline. Administrators get the complete bilingual record with every event, source, and related link, plus access to draft content. Other accounts get a single locale (pass the caller's language in locale): each event's title, summary, media, sources, and related links, plus a canonical URL to the full timeline - never event bodies or the timeline introduction/conclusion.

  ConnectorNo auth