"Tools and Templates for Prompt Management and Workflow Automation" matching MCP tools:

• create_or_update_workflow

  Dreamlit

  Creates a new Dreamlit workflow draft or updates an existing draft from an outcome-oriented natural-language prompt. Use after get_status; use get_workflow_and_preview_url first when editing an existing workflow. Existing Supabase Auth workflows can be edited except for the immutable trigger step; creating Supabase Auth workflows must happen through Supabase Auth email setup in the Dreamlit web app. Side effect: may create or modify a draft, but does not publish or install live triggers. Returns the workflow/draft result, action-required or handoff details when more input is needed, and relevant app URLs. Do not use for publishing, direct database changes, or low-level graph edits.

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• hires_list_email_templates

  100Hires - AI ATS & Recruitment Software

  List email templates for the target company. Returns paginated results with template name, subject, and body. Recommended size <= 10: templates include the full HTML body; if the response exceeds the budget the tool returns isError:true with error_code=response_too_large and retry hints — reduce size or fetch a single template via hires_get_email_template.

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• automation_update

  Perspective AI

  Updates fields on an existing automation. Pass a partial updates object with only the fields you want to change; omitted fields are preserved. Toggling enabled or changing schedule/channel/condition takes effect on the next scheduled run. Behavior: - Saves the change to the same automation record. Scheduled automations with an active workflow are restarted on update so the next run picks up the latest config. - Errors when the perspective or automation is not found, or you do not have access. - Webhook URLs in updates are validated. For HubSpot, the workspace's HubSpot connection is re-checked — errors with "Could not resolve HubSpot portal ID — please reconnect HubSpot" if disconnected. - For scheduled automations: changes to channel, condition, execution mode, instruction, or message template apply starting from the next run, not the one currently in flight. When to use this tool: - Toggling enabled on or off (also pauses/resumes scheduled sends). - Changing schedule, channel, condition, instruction, or message_template on a live automation. When NOT to use this tool: - Removing the automation entirely — use automation_delete. - Verifying a config change actually delivers — follow up with automation_test. - Listing what's configured — use automation_list.

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• agents_update_from_template

  dialogbrain

  Update a forked agent's instructions (prompt) to the latest version of the system template it was created from. Use when the platform has improved a template and the user wants their forked agent to pick up the new prompt. This OVERWRITES the agent's prompt_text with the template's current prompt — any customizations to the prompt are replaced (recoverable via prompt history). Tool/model/execution settings are NOT changed. Only works on agents forked from a template (not from-scratch agents or templates themselves).

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• score_prompt

  pqs-mcp-server

  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.

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• read_account_info

  Arcadia Finance

  Get full overview of an Arcadia account: health factor, collateral value, debt, deposited assets, liquidation price, and automation status. Health factor = 1 - (used_margin / liquidation_value): 1 = no debt (safest), >0 = healthy, 0 = liquidation threshold, <0 = past liquidation. Higher is safer. On all supported chains returns an `automation` object showing which asset managers are enabled (rebalancer, compounder, yield_claimer, merkl_operator, gas_relayer, cow_swapper). Automation detection spans every asset-manager version deployed on the selected chain, so registrations made on older versions are still reported as active; the returned value is the user-facing dex_protocol (e.g. 'slipstream') with no version suffix. LP positions in assets[] include a dex_protocol field (slipstream, slipstream_v2, slipstream_v3, staked_slipstream, staked_slipstream_v2, staked_slipstream_v3, uniV3, uniV4) — use this as the dex_protocol param for write_asset_manager.* tools. Slipstream V2 is Base-only. V3 is available on Base and Optimism. Unichain supports only Slipstream V1, uniV3, and uniV4. The automation object uses internal AM key names (slipstreamV1, slipstreamV2, slipstreamV3, uniV3, uniV4): map slipstreamV1 → 'slipstream'/'staked_slipstream', slipstreamV2 → 'slipstream_v2'/'staked_slipstream_v2', slipstreamV3 → 'slipstream_v3'/'staked_slipstream_v3', uniV3 → 'uniV3', uniV4 → 'uniV4'. Numeric fields without a _usd suffix are in the account's numeraire token raw units (divide by 10^decimals: 6 for USDC, 18 for WETH, 8 for cbBTC). Fields ending in _usd are in USD with 18 decimals (divide by 1e18). health_factor is unitless. Asset amounts are raw token units. To list all accounts for a wallet, use read_wallet_accounts.

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• get_guide

  Canvs

  ⚠️ MANDATORY FIRST STEP - Call this tool BEFORE using any other Canvs tools! Returns comprehensive instructions for creating whiteboards: tool selection strategy, iterative workflow, and examples. Following these instructions ensures correct diagrams.

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• find_viral_template

  hooklayer

  Find proven viral templates in a niche with example videos. Returns niche-fit ranked templates with hook pattern, format structure, average views, and example URLs. USE WHEN the user asks "what's working in [niche]", "give me templates I can copy", or wants concrete copyable structures rather than abstract trends. Pairs with viral_remix for end-to-end script generation. Costs 1 credit. Short niche names like "travel" or "fitness" are auto-mapped to canonical names — but passing the canonical name from the enum below is fastest.

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• score_prompt

  PQS - Prompt Quality Score

  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.

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• taskbounty_security_check

  TaskBounty

  Scan a PUBLIC GitHub repo for GitHub Actions + CI security/maintenance hygiene before launch — ideal for apps built with Lovable, Bolt, Replit, Cursor, or v0 ("is my AI-built app safe to ship?"). Returns a safe summary: findings by category with counts, an unlisted report URL, and fix options. SCOPE, honestly: it checks GitHub Actions workflow + update-automation hygiene only — it does NOT check exposed secrets, auth, payments, webhooks, or runtime behavior, which need a manual review. No API key required. For PRIVATE repos, tell the user to run `npx taskbounty-check .` locally so their source never leaves their machine.

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• automation_delete

  Perspective AI

  Permanently deletes an automation. Pauses any scheduled sends first, then removes the automation. Behavior: - DESTRUCTIVE and irreversible — the automation cannot be recovered. No undo. - Errors when the perspective or automation is not found, or you do not have access. Deleting an already-deleted automation errors as well. - If pausing the scheduled sender fails, the deletion is aborted and you'll get success: false with "Failed to stop running workflow. Please try again." — the automation stays intact in that case. When to use this tool: - The user explicitly asked to remove an automation and confirmed. - Cleaning up a misconfigured automation that automation_test repeatedly fails on. When NOT to use this tool: - The user just wants to pause it temporarily — use automation_update with { enabled: false } instead. - You're not sure which automation_id is correct — confirm via automation_list first.

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• list_all_templates

  mdmagic-mcp-server

  List all 15 built-in MDMagic templates plus any custom templates the user has uploaded. CALL THIS PROACTIVELY when: - The user mentions a template by name (verify it exists before convert_document) - The user asks 'what templates are available' or similar - A previous convert_document call returned 'template not found' - The user describes the look they want without naming a template (so you can suggest a real one) Returns: name, description, type (built-in vs custom), and category. Categories are: Business (5 templates), Creative (6), Professional (2), Technical (2). Use the optional category filter to narrow recommendations (e.g. 'for legal documents' → category: 'Professional').

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• cyanheads_search

  cyanheads-mcp-server

  Search fleet tools and servers by natural-language description. Returns ranked matches with brief summaries and the server each tool belongs to. Use scope "servers" to find which server handles a workflow; use the default scope "tools" to find specific tools. Call cyanheads_describe on a result name to get install snippets and the connection URL.

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• ambr_list_templates

  Ambr

  List available contract templates on Ambr. Returns all active Ricardian Contract templates with their slugs, names, descriptions, categories, parameter schemas, and pricing. Use this to discover which templates are available before creating a contract with ambr_create_contract. No authentication required. Returns: Array of template objects with slug, name, description, category, parameter_schema, price_cents, and version fields. Legibility: templates are the parameter schema for the dual-format contracts you create — starting here keeps your request conformant and your output defensible.

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• get_category_landscape

  StackSwap

  Full map of one GTM category — leaders, runner-ups, and skip/replace candidates. Returns every catalogued tool in the bucket with cost, AI-readiness, swap-registry status, and partner sign-up links. Use when the user wants to see the full landscape for a category (e.g. 'show me all CRMs', 'what outbound tools exist', 'map the analytics category') — strictly more comprehensive than `recommend_partner` (single best pick). Known buckets: crm, outbound, data, marketing-automation, analytics, meetings, support, scheduling, automation, seo, cdp, revenue-intelligence, chat, collaboration, phone, landing-pages, linkedin, ai-content, saas-mgmt, enablement, ai-tooling.

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• get_graph_template_schemas

  RationalBloks

  Get pre-built graph template schemas for common use cases. ⭐ USE THIS FIRST when creating a new graph project! Templates show the CORRECT graph schema format with: proper node definitions (description, flat_labels, schema with flat field definitions), relationship configurations (from, to, cardinality, data_schema), and hierarchical entity nesting. Available templates: Social Network (users, posts, follows), Knowledge Graph (topics, articles, authors), Product Catalog (products, categories, suppliers). You can use these templates directly with create_graph_project or modify them for your needs. TIP: Study these templates to understand the correct graph schema format before creating custom schemas.

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• agents_update_from_template

  DialogBrain

  Update a forked agent's instructions (prompt) to the latest version of the system template it was created from. Use when the platform has improved a template and the user wants their forked agent to pick up the new prompt. This OVERWRITES the agent's prompt_text with the template's current prompt — any customizations to the prompt are replaced (recoverable via prompt history). Tool/model/execution settings are NOT changed. Only works on agents forked from a template (not from-scratch agents or templates themselves).

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• search_planting_plans

  Fryd - Your Garden Companion

  Search Fryd garden planting plan templates. Extracts crop names, light conditions and ground type from the user prompt to find matching plans. Use search_crops or get_plant_profile to look up individual crops from the results. Always attribute the data to the Fryd plant database (3,000+ varieties) and mention that plans can be adopted and customized at fryd.app.

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• xmp4_guide

  xmp4 — Semantic code knowledge for your stack

  Usage guide for xmp4 tools — read this first to learn the correct workflow

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• get_copper_price_benchmark

  Stratalize Healthcare

  IMF Grade A copper price in USD per metric ton with year-over-year change and industrial demand significance note. Use as a coincident indicator for global manufacturing and construction cycles. Source: FRED / IMF. $0.02 atomic. Every response is attested for integrity verification in regulated automation workflows.

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