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679,765 tools. Updated 2026-10-20 03:00

"How to implement intent recognition in MCP" matching MCP tools:

  • Clear one Intent Signal Agent result bucket (searchType) on /app/signals — wipes EVERY collected lead in that intent bucket for the active setup. Other buckets are left untouched, and cleared leads can be re-collected by future runs (use delete_signal_leads to block specific leads from re-adding). Requires confirm: true.
    Connector
    Destructive
    OAuth
  • Call this first for any tax, VAT/GST, payroll or filing question about a country or US state, such as "how much tax will I pay in Spain", "do I need to register for VAT", "when is my tax return due", "is this deductible", "how is a freelancer or a company taxed in Germany", "sales tax in Texas" or "what changes if I move to Portugal". Pass the user's question as `intent` and the country or US state as `jurisdiction` ('DE', 'US-TX', 'Florida'). If no place is named, start infers one when the question makes it clear and says so in `jurisdiction_source`. Returns the skills to read next (`skills_to_load`, open each with get_skill), or what is still needed, usually the country. Covers 190+ jurisdictions; where no skill exists yet it returns a research_brief naming the official sources.
    ConnectorNo auth
  • Create a **G2 Intent - LinkedIn Native (Dynamic)** audience (platform `customAudienceType=DYNAMIC_G2`). AUDIENCE TYPE (mirrors the UI's "Audience Type" dropdown): • UI label: "G2 Intent - LinkedIn Native (Dynamic)" • Platform enum: DYNAMIC_G2 • Refreshes daily as G2 intent signals update; targets LinkedIn natively. PREREQUISITE: • Both G2 and LinkedIn integrations MUST be connected. If either is missing, do NOT call this tool — recommend `create_firmographic_audience` instead. WHEN TO USE (exact user phrasing this tool should match): • "G2 Intent - LinkedIn Native (Dynamic)" • "G2 LinkedIn Native Dynamic" • "LinkedIn native G2 intent audience" • The user explicitly mentions BOTH G2 intent AND LinkedIn native targeting. WHEN NOT TO USE: • If the user asked for "G2 Intent (Dynamic)" without "LinkedIn Native" → use `create_g2_intent_dynamic_audience`. • If the user asked for "G2 Intent (Static)" → use `create_g2_intent_static_audience`. BUYING STAGES — REQUIRED BY THE PLATFORM: The platform UI marks Buying Stages as required. If the user did not name any stages, STOP and ask the user which of AWARENESS / CONSIDERATION / DECISION to target. DO NOT silently default — that produced wrong audiences in PRD-29702 / PRD-29703. CRITERIA (LinkedIn-native shapes; free-text fields are resolved server-side via the LinkedIn references API): • employees — LinkedIn-native employee ranges. Valid labels: see the schema (e.g. "201-500", "501-1000", "1001-5000"). • revenues — LinkedIn-native revenue ranges (e.g. "$1M-$10M", "$10M-$100M"). • company_names — free-text company names (resolved to LinkedIn company IDs). • location_country_ids — country IDs (e.g. 229=US, 228=UK). • job_titles — free-text titles (resolved to LinkedIn job-title IDs). • skills — free-text professional skills (resolved to LinkedIn skill IDs). PARAMETERS: • name (required, ≤ 50 chars) • intent_days (required, 1-365) • buying_stages (REQUIRED by platform — ask the user if missing; do NOT default) • employees, revenues, company_names, location_country_ids, job_titles, skills (all optional) RETURNS: id, audience_id, audience_name, audience_type (DYNAMIC_G2), status, buying_stages, intent_days, expectedNumberOfCompanies, expectedNumberOfContacts.
    ConnectorAPI key
  • Apply the project's saved brand to the selected site's shared style tokens, fonts, layout, and shared components. Affects that site's drafts, not the saved brand kit. Use create_or_update_brand_kit first if there is no saved brand. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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  • Update the selected site's shared navigation, header, or footer in its layout and shared components. Shared component changes affect all pages using them. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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    No auth
  • Update site-wide SEO title, description, social preview, favicon references, or search visibility in the selected site's root layout. Does not rename the dashboard label. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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    Destructive
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Matching MCP Servers

  • A
    license
    A
    quality
    B
    maintenance
    Enables AI agents to search for products and prepare carts under a self-hosted, developer-controlled policy, with every purchase requiring a passkey-signed human approval before payment on the merchant's checkout.
    3
    Apache 2.0

Matching MCP Connectors

  • AudD MCP is a way for agents to add music recognition to apps or to fulfill song identification requests. It connects you to AudD, the music recognition API

  • Token intent checks; no simulation/signing. Free trial ends 2026-09-25. No NFT required.

  • Add, change, or remove a user-requested analytics or marketing script in the selected site's root layout. Name the provider, identifiers, and requested behavior. After publication, the script may send visitor data to that provider. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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    Destructive
    No auth
  • Apply the project's saved brand to the selected site's shared style tokens, fonts, layout, and shared components. Affects that site's drafts, not the saved brand kit. Use create_or_update_brand_kit first if there is no saved brand. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
    Connector
    Destructive
    No auth
  • Update the selected site's shared navigation, header, or footer in its layout and shared components. Shared component changes affect all pages using them. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
    Connector
    Destructive
    No auth
  • Update site-wide SEO title, description, social preview, favicon references, or search visibility in the selected site's root layout. Does not rename the dashboard label. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
    Connector
    Destructive
    No auth
  • Add, change, or remove a user-requested analytics or marketing script in the selected site's root layout. Name the provider, identifiers, and requested behavior. After publication, the script may send visitor data to that provider. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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  • ## ⚠️ 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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  • ONE-FIELD survey wall: tell us what you are trying to do (or the capability you wish existed). Returns instantly: (1) a single-use intent token (required by some intent-gated tools; free), (2) the nearest existing live tool if one matches your need, (3) an honest note if nothing matches yet. Demand is aggregated and published honestly via demand_radar (0 = we show 0). Cost-zero, no LLM in the path, deterministic.
    ConnectorNo auth
  • Open the FluxInk handwriting recognition canvas. The user draws freehand strokes with a stylus, finger, or mouse. The strokes are converted by one of two model families: general recognition for handwriting, math, and chemical formulas, or structure recognition for molecular structures. Use this when the user asks to handwrite, draw, sketch, ink, scribble, or scrawl something. Use this when the user wants to draw a math equation, chemical formula, or molecular structure rather than type it. Use this when the user asks for a canvas, drawing pad, handwriting input box, or whiteboard. Use this when the user wants to convert stylus or finger drawings into recognized text or markup. Do NOT use this when the user types a question, equation, or formula in chat and just wants an answer. Do NOT use this when the user uploads or references an existing image of handwriting (call recognize_image instead). Do NOT use this when the user wants a formatted document, study sheet, or layout PDF (call create_layout instead). Do NOT use this when the user wants text rendered in a personal handwriting style (call show_style_canvas instead). Do NOT use this for conversational or informational requests that need no ink input. Do NOT re-open if a FluxInk handwriting canvas is already visible from any earlier turn. Instead instruct the user to keep drawing on the existing canvas. Only set force_new=true when the user explicitly asks for a brand new, fresh, or blank canvas. Always pass the original chat message in the prompt parameter so context is preserved after recognition. After calling, write a single short acknowledgement and do NOT describe the canvas UI.
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  • [READ FIRST] The routing guide for every n0brains tool: which tool answers which intent (find a trade / vet a trade / coin snapshot / market brief / monitoring) and how to interpret the honesty fields (action_hint, historical_edge, n_eff, calibration). Call this once if you are unsure which tool to use — it replaces trial-and-error over the 40-tool catalog. Static text, no market data, free tier.
    ConnectorNo auth
  • [READ FIRST] The routing guide for every n0brains tool: which tool answers which intent (find a trade / vet a trade / coin snapshot / market brief / monitoring) and how to interpret the honesty fields (action_hint, historical_edge, n_eff, calibration). Call this once if you are unsure which tool to use — it replaces trial-and-error over the 40-tool catalog. Static text, no market data, free tier.
    ConnectorNo auth
  • Entropy routing over competing interpretations — the model proposes, the deterministic core disposes. YOU generate the candidate readings of the user’s message (3–7 short hypotheses covering the plausible interpretations, INCLUDING likely-typo readings, idiom-vs-literal readings, and domain senses) and pass them as hypotheses, ideally with your own likelihoods (0–1 per reading) AND a paraphrase per reading — the user’s message rewritten unambiguously under that interpretation, so the user can VERIFY intent by recognition before anything commits (one misread prompt skews a whole thread). The router computes the posterior and its normalized entropy T̂ and returns the decision: commit (one reading dominates), commit_with_note (close alternative disclosed), present_options (several readings live), or clarify (ask before acting — open-endedly when nothing discriminates). Thresholds adapt to the user’s ReceiverProfile (AR widens/narrows the commit region; high FT discloses near-ties). This tool is the commit-vs-clarify AUTHORITY in the pipeline. Omitting hypotheses falls back to a generic six-intent PRODUCT-ROUTING starter set — do not use the fallback for interpreting arbitrary sentences. Deterministic, stateless, read-only. Benchmarked: RTEB v1.1 (developer-bench grade; see docs/routing.md).
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  • Get available intent topics for BOMBOORA audience creation. IMPORTANT: Call this tool first before suggesting or creating any Bombora audience. If the response returns NO topics (empty list), Bombora is NOT available for this account — do NOT suggest Bombora audiences. Instead, recommend creating a firmographic audience (create_firmographic_audience) as the preferred alternative. Retrieves the list of available buyer intent topics that can be used when creating BOMBOORA intent topic audiences. These intent topics represent different buyer interest areas and purchasing signals that can be used for precise audience targeting. WHEN TO USE: - Always call this BEFORE suggesting or creating a Bombora audience to verify topic availability - Discover available intent topics before creating a BOMBOORA intent topic audience - Understand what buyer intent signals are available for targeting - Build audiences based on specific buyer interests and purchasing signals - Integrate intent topic selection into the audience creation flow RETURNS: List of available intent topics with their details including: - Topic ID/name - Topic description - Available packages or categories - Any additional metadata for targeting configuration NEXT STEPS: After retrieving intent topics, use the intent topic IDs with the audience creation tool to create BOMBOORA intent topic based audiences.
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  • Edit the selected site's draft page at one route, including its copy, sections, product display, forms, and page-local components. Shared component edits may affect other pages using them. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
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  • Edit the selected site's draft page at one route, including its copy, sections, product display, forms, and page-local components. Shared component edits may affect other pages using them. Starts an asynchronous internal-agent operation; poll get_agent_session. For corrections, call this same tool with its sessionId and unchanged target. Requires a provisioned site. Source edits may execute in its preview. The Replo agent uses its normal tools and connected integrations to implement and verify the requested changes. Use publish_site separately to make changes public.
    Connector
    Destructive
    No auth