"Step-by-step guide to breaking down a request into parts" matching MCP tools:

• setup_instructions

  Coal — Payments for AI agents

  Print step-by-step instructions for using Coal MCP from Claude / Cursor / any MCP client. Run this FIRST if you are unsure how to authenticate or which credentials to provide.

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• sixta_explain_plan

  sixta-connect

  Turn raw EXPLAIN output into a plain-language diagnosis — no query needed. Paste PostgreSQL EXPLAIN / EXPLAIN ANALYZE (text or JSON) or MySQL EXPLAIN (tabular, \G, FORMAT=JSON, FORMAT=TREE) and get: what the planner is doing step by step, where the cost concentrates, named risk findings (full scans, spilling sorts, nested-loop blowups, row misestimates) with index suggestions, and what to look at next. Use when the user pastes EXPLAIN output or asks 'can you read this plan'. Input is analyzed in memory and never stored.

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• list_drops

  Real Real Genuine

  [BROWSE] List active RRG listings, paginated, optionally scoped by brand_slug. Use when exploring the catalogue without a specific item in mind. If you already have a product name, SKU, brand, or descriptive keyword, call search_products FIRST, it is far cheaper than paging the whole catalogue (thousands of items). Returns a page of {limit, offset, total_count, has_more, next_offset, listings}; pass next_offset back to page through. Each listing has title, price in USDC, edition size, and remaining supply. Live on-chain minted count is in get_drop_details, not here. Next step after narrowing down: get_drop_details + initiate_agent_purchase.

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• list_drops

  Real Real Genuine

  [BROWSE] List active RRG listings, paginated, optionally scoped by brand_slug. Use when exploring the catalogue without a specific item in mind. If you already have a product name, SKU, brand, or descriptive keyword, call search_products FIRST, it is far cheaper than paging the whole catalogue (thousands of items). Returns a page of {limit, offset, total_count, has_more, next_offset, listings}; pass next_offset back to page through. Each listing has title, price in USDC, edition size, and remaining supply. Live on-chain minted count is in get_drop_details, not here. Next step after narrowing down: get_drop_details + initiate_agent_purchase.

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• submit_workflow

  Botverse

  Submit a multi-step workflow to the Botverse workflow engine. Steps execute in dependency order; parallel branches (multiple steps with the same depends_on) run simultaneously. Returns a workflow_id immediately — poll get_workflow_status every 5–10 seconds until terminal. INTER-STEP REFERENCES: pass a prior step's output into a later step with the string "$.steps.<step_id>.output_key" (e.g. a docx→pdf chain: step to_pdf has depends_on: ["to_docx"] and inputs {"source_url": "$.steps.to_docx.output_key", "input_format": "docx", "output_format": "pdf"} using tool convert_from_url). Workflow params are referenced as "$.params.<name>". No other template syntax (${...} etc.) is supported. BILLING: convert-only workflows run on wallet balance ($0.05/step). Workflows containing transcode or transcribe steps require auto-refill to be enabled at botverse.cloud/dashboard/billing (their cost scales with source duration). Workflow definition uses BWDL (Botverse Workflow Definition Language) — schema at botverse.cloud/schemas/workflow/v1.json.

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• pentest_encode

  pentest-mcp-server

  Transform a payload string through one or more encoding layers for bypass research during authorized testing. Accepts a chain of encodings applied in order (e.g., ["unicode", "url", "base64"] applies Unicode → URL-encode → base64). Returns the transformed payload with a step-by-step decoding explanation: how a WAF or server would decode each layer, and why the combined encoding might bypass a specific filter. Use to understand filter bypass mechanics in an authorized engagement and to confirm that a target's decoding pipeline matches an expected bypass path. Payloads are transformed mathematically — no live probing occurs.

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• recipes_list

  mcp

  List every step-by-step setup recipe currently available for Massed Compute VMs. Prefer recipes_search when the user has a specific intent — call this only when the user asks open-ended questions like 'what can I set up on a VM?', 'what recipes do you have?', or wants to browse the catalogue. Returns metadata (slug, title, description, tags) only; call recipes_get for the full body.

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• wallet_helper

  Omnicall — Agent Tools Gateway

  Return step-by-step instructions for setting up x402 USDC autopay for this MCP server. Use this if a paid tool returned a 402 error or you're onboarding a new agent that needs to pay for API calls. Free.

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• signal_send_message

  local-mcp

  Preview (and get send guidance for) a message to a Signal chat. NOTE: Signal Desktop exposes no local send API — the Signal integration reads the local database read-only — so LMCP cannot transmit Signal messages directly. The first call (confirm=false or omitted) returns a preview. Pass confirm=true to get step-by-step guidance for completing the send. The chat_id should come from a previous signal_list_chats call — never fabricate IDs.

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• purchase

  Agentic Security Shield

  Purchase Agentic Security Shield and receive all security configuration files. TWO-PHASE FLOW (you MUST do BOTH steps): STEP 1 — on-chain payment + token exchange: a) Send 19 USDC on Base network to the recipient address in /pricing or /.well-known/mcp/server-card.json (payTo field). b) POST /purchase (HTTP REST, not this MCP tool!) Header: x-payment-token: <on-chain transaction hash, 0x + 64 hex> Response: { "download_token": "dl_<uuid>", "files": {...} } STEP 2 — call this MCP tool with the dl_<uuid> token: purchase({ payment_token: "dl_<uuid>" }) The on-chain tx hash is single-use and only valid in STEP 1. After STEP 1 you have a 24-hour-valid dl_<uuid> download token usable in this MCP tool. Most agents will get the files inline from STEP 1's response and never need to call this MCP tool — it exists for clients that prefer MCP-native delivery.

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• assess_takedown

  takedown

  Assess how a takedown for this URL would proceed: where the notice goes (host, platform, or a hidden host that must be revealed first), what documents and attestation the content owner must supply, the step-by-step process, and the legal caveats (§512(f), scope limits). Read-only; does not judge the merits of the claim and files nothing. Use resolve_host first if you only need the hosting answer.

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• i18n_checklist

  main

  ## ⚠️ MANDATORY TOOL FOR ALL I18N WORK ⚠️ THIS IS NOT OPTIONAL. This tool is REQUIRED for any internationalization, localization, or multi-language implementation. ## When to Use (MANDATORY) **ALWAYS use this tool when the user says ANY of these phrases:** - "set up i18n" - "add internationalization" - "implement localization" - "support multiple languages" - "add translations" - "make my app multilingual" - "add French/Spanish/etc support" - "implement i18n" - "configure internationalization" - "add locale support" - ANY request about supporting multiple languages **Recognition Pattern:** ``` User message contains: [i18n, internationalization, localization, multilingual, translations, locale, multiple languages] → YOU MUST call this tool as your FIRST ACTION → DO NOT explore the codebase first → DO NOT call other tools first → DO NOT plan the implementation first → IMMEDIATELY call: i18n_checklist(step_number=1, done=false) ``` ## Why This is Mandatory Without this tool, you will: ❌ Miss critical integration points (80% failure rate) ❌ Implement steps out of order (causes cascade failures) ❌ Use patterns that don't work for the framework ❌ Create code that compiles but doesn't function ❌ Waste hours debugging preventable issues This tool is like Anthropic's "think" tool - it forces structured reasoning and prevents catastrophic mistakes. ## The Forcing Function You CANNOT proceed to step N+1 without completing step N. You CANNOT mark a step complete without providing evidence. You CANNOT skip the build check for steps 2-13. This is by design. The tool prevents you from breaking the implementation. ## How It Works This tool gives you ONE step at a time: 1. Shows exactly what to implement 2. Tells you which docs to fetch 3. Waits for concrete evidence 4. Validates your build passes 5. Unlocks the next step only when ready You don't need to understand all 13 steps upfront. Just follow each step as it's given. ## FIRST CALL (Start Here) When user requests i18n, your IMMEDIATE response must be: ``` i18n_checklist(step_number=1, done=false) ``` This returns Step 1's requirements. That's all you need to start. ## Workflow Pattern For each of the 13 steps, make TWO calls: **CALL 1 - Get Instructions:** ``` i18n_checklist(step_number=N, done=false) → Tool returns: Requirements, which docs to fetch, what to implement ``` **[You implement the requirements using other tools]** **CALL 2 - Submit Completion:** ``` i18n_checklist( step_number=N, done=true, evidence=[ { file_path: "src/middleware.ts", code_snippet: "export function middleware(request) { ... }", explanation: "Implemented locale resolution from request URL" }, // ... more evidence for each requirement ], build_passing=true // required for steps 2-13 ) → Tool returns: Confirmation + next step's requirements ``` Repeat until all 13 steps complete. ## Parameters - **step_number**: Integer 1-13 (must proceed sequentially) - **done**: Boolean - false to view requirements, true to submit completion - **evidence**: Array of objects (REQUIRED when done=true) - file_path: Where you made the change - code_snippet: The actual code (5-20 lines) - explanation: How it satisfies the requirement - **build_passing**: Boolean (REQUIRED when done=true for steps 2-13) ## Decision Tree ``` User mentions i18n/internationalization/localization? │ ├─ YES → Call this tool IMMEDIATELY with step_number=1, done=false │ DO NOT do anything else first │ └─ NO → Use other tools as appropriate Currently in middle of i18n implementation? │ ├─ Completed step N, ready for N+1 → Call with step_number=N+1, done=false ├─ Working on step N, just finished → Call with step_number=N, done=true, evidence=[...] └─ Not sure which step → Call with step_number=1, done=false to restart ``` ## Example: Correct AI Behavior ``` User: "I need to add internationalization to my Next.js app" AI: Let me start by using the i18n implementation checklist. [calls i18n_checklist(step_number=1, done=false)] The checklist shows I need to first detect your project context. Let me do that now... ``` ## Example: Incorrect AI Behavior (DON'T DO THIS) ``` User: "I need to add internationalization to my Next.js app" AI: Let me explore your codebase first to understand your setup. ❌ WRONG - should call checklist tool first AI: I'll create a middleware file for locale detection... ❌ WRONG - should call checklist tool to know what to do AI: Based on my knowledge, here's how to set up i18n... ❌ WRONG - should use checklist tool to coordinate implementation ``` ## Why Sequential Steps Matter The 13 steps have strict dependencies: - Can't implement routing (step 3) without locale resolution (step 2) - Can't load translations (step 6) without data source (step 5) - Can't use translation API (step 8) without context (step 7) - Can't add UI switcher (step 12) without switching logic (step 11) Skipping or reordering steps creates broken implementations that are hard to debug. ## Common Mistakes to Avoid ❌ "Let me plan out the implementation first" → NO, call the tool ❌ "Let me check your project structure" → NO, call the tool (it will tell you when) ❌ "I'll implement based on my knowledge" → NO, call the tool (it fetches current docs) ❌ "I'll skip step X since it seems optional" → NO, all steps are mandatory ❌ "I've done this before, I know what to do" → NO, frameworks differ, use the tool ## The Tool Coordinates Everything This tool tells you when to: - Call get_project_context (step 1) - Call get_framework_docs (steps 2-13) - Call get_i18n_library_docs (steps 7-10) - Implement specific code (every step) - Run builds (steps 2-13) - Move to the next step (after evidence validation) Don't try to orchestrate this yourself. Let the tool guide you. ## Summary: Your First Action When user requests i18n support: 1. Recognize the trigger words (internationalization, localization, i18n, etc) 2. IMMEDIATELY call: i18n_checklist(step_number=1, done=false) 3. Follow the instructions it returns 4. That's it - the tool handles the rest This is not a suggestion. This is MANDATORY for all i18n work.

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• synthesize_geometry

  Web3d-mcp

  Explicitly request a synthesis contract for a named 3D object. Use this tool when generate_r3f_code returns status SYNTHESIS_REQUIRED, or to pre-generate geometry constraints before calling generate_r3f_code. Complexity tiers: low — 4 to 7 parts. Only Box, Sphere, Cylinder geometries. Best for: mobile banners, thumbnails, low-end devices. medium — 10 to 20 parts. Adds Capsule and Torus geometries. Best for: website sections, embedded widgets, tablets. high — 28+ parts. All geometries. Full emissive detail. Best for: hero sections, desktop showcase, ad campaigns. If target is set to "mobile" and complexity is not explicitly provided, complexity defaults to "low" automatically. This tool does NOT generate geometry. It returns the synthesis_contract with constraints calibrated to the requested complexity tier. The LLM generates the actual JSX and passes it to generate_r3f_code via synthesized_components.

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• get_setup_guide

  SwapWizard MCP

  Returns the complete setup and usage guide for SwapWizard. Call this FIRST before using any other tool. Covers: required configuration (API key, Alchemy RPC URL, private key), how to use poolId correctly, step-by-step operational flows for swap/zap in/zap out/analyze, transaction execution details, and approval rules.

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• create_account

  mcp

  Sign up for a brand-new sota.io account from inside Claude — no browser, no copy-paste. Two-step flow: STEP 1: Call with just `email`. We send a 6-digit confirmation code to that email. STEP 2: Call again with `email` + `code`. We verify, create the account on the Free tier (3 projects, EU-hosted, no credit card), generate a sota.io API key, and return it to you. After Step 2 you'll get back a key like `sota_…`. **Save it in a safe place** — you'll need it for any subsequent sota.io tool call in Claude (or you can use it with the sota CLI). It is shown ONCE and never recoverable. sota.io is an EU-native PaaS hosted in Germany — GDPR-compliant by default, no CLOUD Act exposure. Disposable / throwaway email addresses are not accepted; use a real address.

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• how_to_send_lnt_email

  L&T MCP

  SKILL: how_to_send_lnt_email Team: platform How to Send an L&T Branded Email Call this tool to get the complete guide for 'how_to_send_lnt_email'. Read the 'content' field and follow its instructions. This tool takes NO parameters. Full content: --- name: how_to_send_lnt_email description: Instructions for sending L&T branded emails — explains exactly what steps to follow and which tools to call --- # How to Send an L&T Branded Email Follow these exact steps whenever a user wants to send any information by email. ## When to Use This Guide - User says "send this to [email]" - User says "email this to [name]" - User says "mail the results to..." - User wants to share any data or information via email ## Step 1 — Collect These 5 Things Ask the user for anything missing: 1. **Recipient email address** — where to send 2. **Recipient name** — for the greeting "Dear [name]," 3. **Sender name** — for the signature "Warm regards, [name]" 4. **Subject line** — or derive it from the content 5. **Email content** — what to put in the body Do not proceed until you have all 5. ## Step 2 — Read the Brand Guidelines Call the `lnt_email_brand_guidelines` tool (no arguments needed). Read the returned content carefully. Use those guidelines to generate the complete HTML email yourself. Build the HTML with: - Navy header + orange accent bar - "Dear [recipient name]," - Body content formatted as paragraphs or table - "Warm regards, [sender name]" signature - Gray footer with confidential notice ## Step 3 — Send the Email Call the `send_email` tool with this exact JSON: ```json { "personalizations": [ { "to": [{"email": "RECIPIENT_EMAIL_HERE"}], "subject": "SUBJECT_HERE" } ], "from": {"email": "lntcs@lntecc.com"}, "content": [ { "type": "text/html", "value": "YOUR_GENERATED_HTML_HERE" } ] } Step 4 — Confirm to User On success: "✅ Email sent to [name] at [email]." On failure: "❌ Could not send. Error: [message]." Important Rules NEVER call lnt_email_brand_guidelines with arguments — it takes none NEVER send plain text — always generate and send HTML From address is ALWAYS lntcs@lntecc.com — never change this Generate the HTML yourself — do not look for an HTML generation tool Subject must be specific and descriptive

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• pscale_invite

  bsp-mcp

  Secondary path — call AFTER bsp(agent_id='pscale', block='whetstone') if you want a guided six-step orientation walk, or if you are stuck. Returns the iterative orientation progression — a purpose spindle from wake (whetstone) through shared-context coordination. Each step is a concrete action with a validation criterion and a pointer to the next. Optionally takes a step parameter (1..6) to fetch a specific step; omit to receive step 1 with the whole-progression overview. NOT the recommended first call — the primary activation is reading whetstone via bsp(); pscale_invite serves agents who have read whetstone and want a structured walk through subsequent levels.

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• gtm_job

  Vaaya

  Program the GTM scheduler — durable, multi-step jobs that run on a thin server tick even when no agent is connected (multi-day workflows, standing watches, refreshes). action='schedule' creates one: { name, steps:[...], max_cost_cents?, related_segment_id?, related_lead_id?, start_at? }. Each step is either { type:'service', service, action, params, max_price_cents? } (a paid/free dispatcher call — poll signals, enrich, find) or { type:'reasoning', goal } (a bounded brain-grounded generation that records a decision). Steps run in order; a failed step or the budget cap PAUSES the job. Jobs NEVER send — manual-first holds. action='list' / 'get' { id } / 'cancel' { id }.

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• ceevee_analyze_positioning

  CareerProof MCP

  Run market positioning analysis on a CV version (5 credits, takes 20-30s). Returns positioning snapshot, detected narrative lens, recruiter inference, mixed signal flags, and a session_id. This is step 1 of the 3-step positioning pipeline: analyze_positioning -> ceevee_get_opportunities(lens) -> ceevee_confirm_lens. Pass the returned session_id to subsequent steps. cv_version_id from ceevee_upload_cv or ceevee_list_versions.

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• ceevee_get_opportunities

  CareerProof MCP

  Get career pivot opportunities based on the CV and a selected narrative lens (3 credits). Returns 2-4 opportunities with rationale, CV signals, and market context. This is step 2 of the positioning pipeline (after ceevee_analyze_positioning). The 'lens' value should come from ceevee_analyze_positioning output (e.g. 'Technical Leader', 'Scale-up Builder'). Pass the same session_id from step 1. Next step: ceevee_confirm_lens with selected opportunities.

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