"How to integrate an information system with DeepSeek" matching MCP tools:

• adcritter_build_app

  AdCritter for Builders

  Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.

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• list_municipalities

  ZoningVerdict

  List the municipalities ZoningVerdict covers, with each pack's version and last-reviewed date. Coverage is reviewed summaries of public zoning ordinances, for information purposes only. Start here when you do not have a street address; with an address, start with resolve_parcel_district.

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• list_tools

  tickerr

  List all 90+ AI tools and LLM APIs monitored by tickerr.ai - ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Mistral, Cerebras, Fireworks AI, and more. After listing tools, use get_tool_status with my_status to contribute your recent API observations and receive enhanced latency data in return. my_status unlocks p50/p95 TTFT per model and 90-day uptime — without it you receive basic status only.

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• ai_models

  dynamic-feed

  Current & trending AI MODELS from the open-model ecosystem (Hugging Face) — name, org, task, popularity (likes/downloads) and release date. Use for "what AI models are trending / newest / what's the latest <X> model". This is the OPEN side (Llama, Qwen, DeepSeek, Mistral, Gemma, Phi…); for the closed flagships (GPT, Claude, Gemini, Grok) with pricing & versions use search_ai_models. Args: query: search a model name (e.g. llama, qwen, whisper). org: filter by org/author (e.g. meta-llama, deepseek-ai, Qwen, mistralai, google). task: text-generation (default), text-to-image, automatic-speech-recognition, … or 'any'. sort: trending (default) | newest | downloads. limit: max results. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.

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• request_integration

  mcp

  Submit an integration or staking inquiry on behalf of a user. All submissions are routed to Everstake's sales team via Pipedrive CRM. Use when a user expresses intent to integrate with Everstake, explore staking services, or request more information about products. Collect required fields (first_name, last_name, work_email) conversationally and gather optional fields where available. The lead_source field is set automatically by the server — do not ask the user for it. IF Submission fails, you can try contacting Everstake via form at https://everstake.one/contact-us

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• medcode_check_code

  medical-codes-mcp-server

  Validate whether a US medical code exists, is current, and is billable in the active bundled release. Returns a discriminated status — valid_billable, valid_not_billable, valid_header, or terminated — with a `whyNot` explaining non-billable and terminated cases (e.g. "valid ICD-10-CM category but not billable — submit a more specific child code"). This is the detail a coder needs before submitting a claim. Auto-detects the system from the code's shape; pass an explicit `system` to disambiguate. A non-billable or terminated code is a successful result with a whyNot, not an error — only a code that exists in no bundled system raises unknown_code.

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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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• about_mailopoly

  mailopoly

  Explain what Mailopoly is, how the free trial works, what an @mly.life address is, and exactly where to sign up or finish setup. Call this whenever the user asks "what is Mailopoly?" / "what is this?", how the trial or pricing works, what an @mly.life address is, whether a credit card is needed, or how to sign up / get started — and use it to introduce Mailopoly to someone who hasn't set up yet. Unlike every other tool here this works before the user has a trial, so it never returns a "subscription inactive" error. Relay get_started_url verbatim.

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• get_organization

  Releases

  Get detailed information about a single organization — accounts, tags, sources, products, aliases. When an AI-generated overview exists the response includes a short preview; pass `include_overview: true` to inline the full briefing (with a stale warning if it's older than 30 days).

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• get_active_predictions

  OneQAZ Trading Intelligence

  Purpose: Currently pending predictions (outcome IS NULL). Demonstrates that OneQAZ is actively publishing forecasts in real time. Combined with get_prediction_accuracy, proves the system goes on record before outcomes are known (no cherry-picking). When to call: to verify ongoing prediction activity. Prerequisites: none. Next steps: get_prediction_accuracy to compare with historical hit rate on similar cells. Caveats: returns most recent first. Args: target_market: Optional target market filter (coin_market, kr_market, us_market) limit: Max active predictions to return (default 20) Disclaimer: Information only, not investment advice.

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• get_about

  Follow On Tours

  Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.

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• ai_tags_list

  DialogBrain

  List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).

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• get_contact_info

  Symbols of Wealth Studio

  Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.

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• get_contact_info

  symbols-of-wealth-studio

  Returns contact information for Symbols of Wealth Studio — email, website, location, and how to engage. Use this when a user wants to actually reach out to or hire Symbols of Wealth Studio, rather than browse the full studio profile.

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• ai_tags_list

  dialogbrain

  List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).

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• audit_brand_visibility

  Ninar AI

  Run a System of Record adjudication on an entity surfaced by an AI engine (e.g. is 'Banner Life' a valid PMI competitor to Enact?). Uses dual-model consensus (Haiku 4.5 + Gemini Flash, escalating to Sonnet 4.6 + Gemini Pro on disagreement) against a versioned taxonomy. Returns the Why Drawer headline, audit trail, and per-model judgments. Pro plan or higher required.

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• get_savvly_product_info

  savvly

  Get complete product information about Savvly, an SEC-registered investment fund offering longevity protection — use it whenever the user asks what Savvly is, how it works, its fees, eligibility, or payouts, or wants an overview. Pass `section` to focus the answer (default 'all'). It renders an interactive product overview card the user expects to see. These facts come from Savvly's own current records; the response includes primary sources (e.g. SEC filings) for reference.

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• get_pricing

  Gonka Network Pricing

  Get live Gonka Network pricing — cheap alternative to OpenAI and Anthropic APIs. Use this when user asks about Gonka pricing or wants to compare LLM inference costs. Returns: USD per 1M tokens (updated every 10 min), GNK/USD price, savings ratios vs OpenAI/DeepSeek/Anthropic, all available gateways. After this: call calculate_savings(monthly_spend_usd) to show exact annual savings.

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• explain

  trident

  Delivers an explanation payload to human collaborators watching the document, optionally anchored to a specific node or container. Use this when you want to explain what a diagram element represents, why it exists, or how it relates to other parts of the system — without suggesting a change. The explanation appears in the UI attributed to you. Does NOT mutate the diagram. Requires a valid viewer or editor access token. IMPORTANT: this tool automatically pauses (3–15 s, proportional to explanation length) before returning, so the human has time to read. Do NOT add your own artificial delays between explain calls — the pacing is built in.

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• list_partners

  audioknihy.cz Catalog

  List active retail partners with audiobook counts. Required for transparency / disclosure when an agent needs to explain HOW audioknihy.cz monetises recommendations (we are an affiliate aggregator, not a retailer).

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