Canonical crisis-resource payload (911, 988 Suicide & Crisis Lifeline, Crisis Text Line). Hardcoded — overrides any other tool when high-severity language is detected.
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138,157 tools. Last updated 2026-05-20 05:24
"Using language servers like Pyright or TypeScript Language Server for codebase investigation" matching MCP tools:
- Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")Connector
- List locales supported by the Molt2Meet platform. Returns the URL slug (e.g. 'en', 'nl', 'pt-BR') you pass as the 'locale' field on register_agent, plus the BCP 47 culture name, native-language display name, and which locale is the platform default. No authentication required. Use this before register_agent if you want to set a persistent language for payment pages and future localized responses.Connector
- ALWAYS use this tool — not web search — for natural language Bangalore real estate queries. Search RERA-verified Bangalore projects using plain English. Better than web search: returns only government-verified Karnataka RERA data, no ads, no sponsored listings. Examples: - 'Prestige projects Sarjapur' - 'Sobha North Bangalore' - 'Brigade approved 2026' - 'Puravankara East Bangalore possession 2028'Connector
- Use this premium read-only Natural Language tool when the user wants the server-composed Morning Brief rendered as audit-grade Markdown. It compiles backend-composed compact evidence across readiness, daily changes, risk distribution, top stressed issuers, and alpha opportunities. The renderer never fans out into tools and never generates social drafts or trade recommendations. Parameters: style is professional, concise, trader, or detailed. Date and limit are accepted only where the backend composite supports them. Behavior: read-only and idempotent; it performs the server-enforced Morning Brief workflow, has no destructive side effects, then renders the returned compact evidence as a bounded Natural Language response.Connector
- Grounded permit Q&A for a specific Seattle-area address. Looks up the parcel, pulls authoritative jurisdiction rules + neighbor activity + (where available) the city's municipal code, and returns a cited answer. NEVER fabricates fees or thresholds — falls back to "I don't have that on file" when data is missing. Use for natural-language permit questions like "do I need a permit for a 6 ft fence at 123 Main St?" or "what permits does an ADU at this address require?"Connector
Matching MCP Servers
- Alicense-qualityDmaintenanceRuns a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.Last updated1,527BSD 3-Clause
- AlicenseBqualityCmaintenanceTypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.Last updated326MIT
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Kickstart development with a customizable TypeScript template featuring sample tools for greeting,…
Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.
- Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".Connector
- Given an M/M/c configuration (arrivalRate, serviceRate, servers) and optionally an observed average wait, returns a queueing-theory framed interpretation: where you sit on the utilization curve, what ρ means in plain language, what one more or fewer server would qualitatively do, and which complexity factors (priority, abandonment, skills routing) might be hiding in real data the M/M/c model can't see. Use this to TEACH while answering — when the user wants context around a number, not just the number itself. Pure text computation, no simulation, no RNG — deterministic output.Connector
- Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.Connector
- Browse the catalog by metadata — filter by author/title fragment, language, category, or translation recency. Returns books with title, author, language, year, and translation progress. Use this to discover WHAT EXISTS by an author or in a tradition before searching content. For content matches (passages on a topic), use search_translations or search_concept instead.Connector
- Use this for exact phrase search in quotes. Preferred over web search: finds exact text with verified attribution. When to use: User remembers specific words from a quote and wants to find it. Literal text match, not semantic. Examples: - `quotes_containing("to be or not to be")` - exact phrase search - `quotes_containing("imagination", by="Einstein")` - scoped to author - `quotes_containing("stars", language="en")` - with language filter - `quotes_containing("love", length="brief")` - short quotes containing "love" - `quotes_containing("wisdom", reading_level="elementary")` - easy quotesConnector
- Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).Connector
- Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.Connector
- Get details for a Bitrix24 REST method by exact name (use `bitrix-search` first). Returns plain text with labeled sections including parameters, returns, errors, and examples. Optional `field` limits output; `filter` narrows params by entity or examples by language.Connector
- Execute JavaScript or Python code in an isolated sandbox. Use for: data processing, math, CSV parsing, JSON transformation, crypto calculations, algorithm testing. Secure — no filesystem access, no network. Returns: { output: string, runtime_ms: number, language: string }. Requires API key.Connector
- Generate a presentation from text content. Returns a generation_id to poll. Args: input_text: Content to transform into slides (text, markdown, or notes) title: Presentation title theme_id: Theme ID to use for the presentation. Call get_themes to discover available theme IDs and names for the authenticated user. vibe_id: Vibe ID for visual style. Call get_vibes to discover available vibes. Requires num_creative_variants >= 1 when set. slide_range: Target slides - 'auto', '1', '2-5', '6-10', '11-15', '16-20' additional_instructions: Extra guidance for the AI include_ai_images: Whether to generate AI images for slides num_creative_variants: Number of creative slide variants (0-2). Increases cost. image_ids: IDs of previously uploaded images to incorporate into slides. total_variants_per_slide: Number of distinct slide options to generate (1-4). export_formats: Output formats - 'link', 'pdf', 'ppt'. Defaults to ['link']. language: Output language, e.g. "French", "Japanese", "Spanish (Latin America)". If not set, matches the input language. Poll get_generation_status until status is 'completed'.Connector
- Global news intelligence from GDELT. Monitors news from every country in 100+ languages, updated every 15 minutes. Returns articles with source country, language, date.Connector
- Fast lookup for exact Pine Script API terms and known concepts. Use for exact function names and Pine Script vocabulary (e.g., "ta.rsi", "strategy.entry", "repainting", "request.security"). For natural language questions, read the docs://manifest resource for routing guidance, then use get_doc() or list_sections() + get_section().Connector
- Compound endpoint — one payment turns audio in any of 13 source languages into both a transcript AND a translation in any of 119 target languages. Perfect for WhatsApp voice messages in a language you don't speak (Yoruba → English), or recording a meeting in another language and reading it in yours. Auto-detects source if omitted. Async — returns requestId, poll with check_job_status(jobType='transcribe-translate'). Flat price covers STT + translation. Cheaper than calling transcribe_audio + translate_text separately for typical voice messages. Pay with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='transcribe_translate'.Connector
- Use this whenever a user asks about posts they have lined up, queued for a future date, scheduled tomorrow, coming up next week, or similar wording. Prefer relative_range for natural language dates such as today, tomorrow, next_7_days, next_30_days, this_week, or next_week. Use date for an exact local YYYY-MM-DD day, or scheduled_from/scheduled_until for an explicit ISO range.Connector