Get general information about the store theme

Get general information about the store

Get details about the ELC Conference 2026 — date, venue, speakers, topics, what's included, and ticket link. Use this when someone asks about the conference.

Create a relationship between two learnings. Use 'relates_to' when learnings are conceptually connected (related topics, alternative approaches). Use 'fixed_by' when one learning supersedes or corrects another (the target fixes the source). Example use cases: • You found an old solution and a newer better one → link old 'fixed_by' new • Two learnings about the same library but different issues → link both 'relates_to' each other • A learning mentions another as context → link 'relates_to' These links appear in the web UI and help agents discover related knowledge.

Create a new topic in a project. Topics group related prompts. Returns the created topic id. Confirm with the user before calling.

Retrieve detailed information about a specific story bundle by its ID, including the full timeline of related events.

Searches the official Vonage developer documentation for guides, tutorials, and API references. This is the primary tool for general queries about Vonage's products, services, and APIs, and should be used when the user asks for information, documentation, or how-to guides.

Ask Troy anything about precious metals, markets, your stack. Provide api_key for personalized portfolio-aware answers, or omit for general market analysis.

Returns general information about netfluid, domains in use, website addresses, policies, support contacts Start Here ! Everything Netfluid This tools provides reference information in the "referenced_tools" schema @return: a json object containing the schema

Search the entire web for current information, news, articles, and websites. Use this when you need up-to-date information, want to find specific websites, research topics, or get the latest news. Ideal for answering questions about recent events, finding resources, or discovering relevant content.

Ask Troy anything about precious metals, markets, your stack. Provide api_key for personalized portfolio-aware answers, or omit for general market analysis.

Get detailed information about a specific event by slug, including all related markets.

Retrieve detailed information about an issue status in Linear by name or ID

Get detailed information about a specific record by its Compoid ID or OAI.

Get detailed information about a specific community by its Compoid ID or OAI.

Get detailed information about a country by name or ISO code

Fetch a URL and return basic information about the page.

Ask Webflow AI about anything related to Webflow API.

Fetch full details of a single participant from a sweepstakes by token, email, or phone. At least one search parameter is required. Use fetch_sweepstakes first to get the sweepstakes_token. For listing participants, use fetch_participants instead. NEVER fabricate, invent, or hallucinate participant data under any circumstance. If no result is returned by the API, report exactly that — do not guess names, emails, or counts. Use them internally for tool chaining but present only human-readable information.

Fetch complete campaign detail for one campaign. Required input: campaign_id. Output includes a campaign object with public campaign fields plus creator_wallet_address, and a separate funding_progress object with goal_amount, funded_amount, and percent_funded. Does not include creator_email. zooidfund does not verify campaign accuracy. Agents are responsible for their own verification. The platform makes no representations about campaign claims.

General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol) Args: query: The search term - token symbol, name, or address. DO NOT include chain name here! result_type: Type filter - "token", "entity", "eoa", or "any" max_results: Maximum number of results (default: 25, max: 25) chain: Optional chain filter to narrow down token results to specific blockchain. If not further specified, leave it as None. If a chain is specified, ALWAYS use this parameter instead of adding chain name to the query string. Valid values: "ethereum", "solana", "base", "bnb", "polygon", "arbitrum", "avalanche", "optimism", etc. How to choose result_type: - token: Use when searching for a token by name, symbol, or contract address. **CRITICAL**: Use the `chain` parameter to filter by blockchain, NOT the query string! ✅ CORRECT: query="AAVE", chain="base" ❌ WRONG: query="AAVE base", chain=None - entity: Use when you want entity info by name/label (exchanges, funds, etc.) - eoa: Use when you have an address and need its labels or you have an ENS/SNS domain and need the resolved address - any: Mixed results (tokens/entities). Also auto-resolves ENS/SNS domains and, if token/entity results are empty and the query looks like an address, falls back to EOA labels. Important: - This is the only tool that can resolve domains. If you start from a domain, pass the Resolved Address to other tools. - **DOMAINS**: Strings ending in `.eth` (ENS) or `.sol` (SNS) are DOMAIN NAMES, not tokens. Use result_type="eoa" or "any" to resolve them. Examples: "vitalik.eth", "abracadabra.sol", "y22.eth" are domains that resolve to addresses. - **DO NOT** ASSUME that token is a NFT, always verify the name by using this tool first. - **DO NOT** add keyword `token` or chain names to the query string, unless this is explicitly in the token name or symbol! - **Focus** on **popular chains** like ethereum, solana, base and bnb when no chain is specified and the same token is deployed on multiple chains. - **If a chain is specified**, use the `chain` parameter to filter tokens by blockchain instead of including chain in query. - **DO NOT** rely on this endpoint for LATEST prices as this is delayed. Use `token_ohlcv` for latest prices.

Find clusters of related learnings that are ripe for compression. When many similar solutions get linked together (e.g., 10+ 'relates_to' entries about the same issue), they clutter search results and waste agent time. Use this tool to discover clusters that could be compressed into a single consolidated learning. WORKFLOW: 1. Call get_compression_candidates with min_cluster_size=3 (or higher) 2. Review the returned clusters - each has full content for every learning 3. Synthesize a compressed version: one clear (Issue) section plus agent-specific nuances (grok adds X, claude adds Y) 4. Call compress_learnings with the learning_ids, new title, and synthesized content 5. Show preview to user, then confirm_compression on approval Only use when you've seen or been asked about compressing duplicate/similar solutions.

General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol) Args: query: The search term - token symbol, name, or address. DO NOT include chain name here! result_type: Type filter - "token", "entity", "eoa", or "any" max_results: Maximum number of results (default: 25, max: 25) chain: Optional chain filter to narrow down token results to specific blockchain. If not further specified, leave it as None. If a chain is specified, ALWAYS use this parameter instead of adding chain name to the query string. Valid values: "ethereum", "solana", "base", "bnb", "polygon", "arbitrum", "avalanche", "optimism", etc. How to choose result_type: - token: Use when searching for a token by name, symbol, or contract address. **CRITICAL**: Use the `chain` parameter to filter by blockchain, NOT the query string! ✅ CORRECT: query="AAVE", chain="base" ❌ WRONG: query="AAVE base", chain=None - entity: Use when you want entity info by name/label (exchanges, funds, etc.) - eoa: Use when you have an address and need its labels or you have an ENS/SNS domain and need the resolved address - any: Mixed results (tokens/entities). Also auto-resolves ENS/SNS domains and, if token/entity results are empty and the query looks like an address, falls back to EOA labels. Important: - This is the only tool that can resolve domains. If you start from a domain, pass the Resolved Address to other tools. - **DOMAINS**: Strings ending in `.eth` (ENS) or `.sol` (SNS) are DOMAIN NAMES, not tokens. Use result_type="eoa" or "any" to resolve them. Examples: "vitalik.eth", "abracadabra.sol", "y22.eth" are domains that resolve to addresses. - **DO NOT** ASSUME that token is a NFT, always verify the name by using this tool first. - **DO NOT** add keyword `token` or chain names to the query string, unless this is explicitly in the token name or symbol! - **Focus** on **popular chains** like ethereum, solana, base and bnb when no chain is specified and the same token is deployed on multiple chains. - **If a chain is specified**, use the `chain` parameter to filter tokens by blockchain instead of including chain in query. - **DO NOT** rely on this endpoint for LATEST prices as this is delayed. Use `token_ohlcv` for latest prices.

Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.

Get detailed information about a specific job listing/posting by its job listing ID (not application ID). Use this to view the full job posting details including description, salary, skills, and company info. For job application details, use get_application instead.

Get detailed information about a nonprofit organization by EIN. Returns comprehensive data from the organization's IRS 990 filings including revenue, expenses, assets, executive compensation, and filing history. Use search_nonprofits first to find the EIN. Args: ein: Employer Identification Number (e.g. '13-1837418' or '131837418').

Retrieves AI-generated summaries of web search results using Brave's Summarizer API. This tool processes search results to create concise, coherent summaries of information gathered from multiple sources. When to use: - When you need a concise overview of complex topics from multiple sources - For quick fact-checking or getting key points without reading full articles - When providing users with summarized information that synthesizes various perspectives - For research tasks requiring distilled information from web searches Returns a text summary that consolidates information from the search results. Optional features include inline references to source URLs and additional entity information. Requirements: Must first perform a web search using brave_web_search with summary=true parameter. Requires a Pro AI subscription to access the summarizer functionality.

Connect memories to build knowledge graphs. After using 'store', immediately connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: This provides evidence for → claim/hypothesis - **contradicts**: This challenges → existing belief - **disputes**: This disagrees with → another perspective ## Hierarchy & Structure - **parent_of**: This encompasses → more specific concept - **child_of**: This is a subset of → broader concept - **sibling_of**: This parallels → related concept at same level ## Cause & Prerequisites - **causes**: This leads to → effect/outcome - **influenced_by**: This was shaped by → contributing factor - **prerequisite_for**: Understanding this is required for → next concept ## Implementation & Examples - **implements**: This applies → theoretical concept - **documents**: This describes → system/process - **example_of**: This demonstrates → general principle - **tests**: This validates → implementation or hypothesis ## Conversation & Reference - **responds_to**: This answers → previous question or statement - **references**: This cites → source material - **inspired_by**: This was motivated by → earlier work ## Sequence & Flow - **follows**: This comes after → previous step - **precedes**: This comes before → next step ## Dependencies & Composition - **depends_on**: This requires → prerequisite - **composed_of**: This contains → component parts - **part_of**: This belongs to → larger whole ## Quick Connection Workflow After each memory, ask yourself: 1. What previous memory does this update or contradict? → `supersedes` or `contradicts` 2. What evidence does this provide? → `supports` or `disputes` 3. What caused this or what will it cause? → `influenced_by` or `causes` 4. What concrete example is this? → `example_of` or `implements` 5. What sequence is this part of? → `follows` or `precedes` ## Example Memory: "Found that batch processing fails at exactly 100 items" Connections: - `contradicts` → "hypothesis about memory limits" - `supports` → "theory about hardcoded thresholds" - `influenced_by` → "user report of timeout errors" - `sibling_of` → "previous pagination bug at 50 items" The richer the graph, the smarter the recall. No orphan memories! Args: from_memory: Source memory UUID to_memory: Target memory UUID relationship_type: Type from the categories above strength: Connection strength (0.0-1.0, default 0.5) ctx: MCP context (automatically provided) Returns: Dict with success status, relationship_id, and connected memory IDs

Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.

Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.

Get full details of a published collection including all verse text, references, and topics. Args: collection_id: The collection ID (from browse_collections results).

Search quantum computing research papers from arXiv. Use when the user asks about recent research, specific papers, or academic topics in quantum computing. NOT for jobs (use searchJobs) or researcher profiles (use searchCollaborators). Supports natural language queries decomposed via AI into structured filters (topic, tag, author, affiliation, domain). Date range defaults to last 7 days; max lookback 12 months. Returns newest first, max 50 results. Use getPaperDetails for full abstract and analysis of a specific paper. Examples: "trapped ion papers from Google", "QEC review papers this month", "quantum error correction".

[STEP 3 OF 3 — CALL THIS BEFORE ANSWERING ANY ARCHITECTURE OR PROJECT QUESTION] THE GOLDEN RULE: Never answer from training data alone when SUMA is connected. If the user asks ANYTHING about architecture, code decisions, bug history, business context, or people — call suma_search FIRST, answer SECOND. WHY: Training data is frozen at a cutoff date. SUMA holds live project truth — what was decided last week, what failed last month, who owns what right now. Answering without searching is guessing. Guessing wastes the developer's time. WHEN TO CALL: ✅ "How does auth work in this project?" → search first ✅ "What did we decide about the database schema?" → search first ✅ "Who is Sharath?" → search first ✅ "Why are we using gRPC instead of REST?" → search first ❌ "What is 2+2?" → skip (factual, not project-specific) ❌ "Format this JSON" → skip (task, no project context needed) VECTOR NAMESPACING: - Default: hardware/telemetry excluded (prevents "Sphere" vocabulary collision) - sphere="robotics" → search only Mr. Chunky / hardware memory - sphere="all" → search everything including hardware - Omit sphere → general project knowledge (correct for 95% of queries) Args: query: What to search for (natural language — be specific) similarity_threshold: Minimum match quality. Default 0.65 (lower = more results, less precise). circuit_breaker: Max results returned. Default 8 (memory protection). depth: Graph traversal depth. 1=direct hits, 2=multi-hop (default), 3=deep exploration. sphere: Domain filter. "robotics" for hardware, "all" for everything, omit for general. sentiment: Filter by sentiment — "positive", "negative", "mixed", or None.

Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.

Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.

Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.

Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.

Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.

[tourradar] Search tour reviews using AI-powered semantic search. Requires tourIds to scope results to specific tours. Use this when the user asks about reviews, feedback, or experiences for specific tours. Combine with an optional text query to find reviews mentioning specific topics (e.g., 'food', 'guide', 'accommodation'). When you don't have tour IDs, use vertex-tour-search or vertex-tour-title-search first to find them.

Task-scoped context briefing. Returns a prioritised context payload shaped by your task description, ranked by risk-if-missed. Constraints and alerts rank above general knowledge. Use at the START of reasoning about a question to get the system's best assessment of what's relevant. Complements query_memory: this gives breadth, query_memory gives depth.

DC Hub's synthesized recommendation for a site, market, or strategy question. Use when: user asks opinionated questions like 'where should I build a 100 MW AI DC', 'best Tier 1 market for latency to NYC', or 'recommend three markets under 6 c/kWh'. Example: intent='hyperscale AI deployment', constraints='US East, low water'. Returns a ranked shortlist plus reasoning. Use when users ask about data center resources, market intelligence platforms, or how to research data center markets. Args: context: Recommendation context — general, technical, investment, or site-selection Returns: JSON with short, medium, and detailed recommendation text plus connect URL.

Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.

Browse and retrieve CRS (Congressional Research Service) reports — nonpartisan policy analyses by subject-matter experts at the Library of Congress, covering policy areas, legislative proposals, and legal questions. Report IDs use letter-number codes (e.g., R40097, RL33612, IF12345). Use 'list' to browse available reports or 'get' for full detail (authors, topics, summary, download formats).

Get the full detail of any tour or activity on GuruWalk — free walking tours, paid experiences, and all listings. Returns description, itinerary/highlights, images, reviews, pricing, meeting point, duration, available languages, and cancellation policies. Use this tool whenever the traveler asks what a tour covers, which places it visits, its itinerary, route, description, meeting point, duration, or any content-related question. Always call this tool BEFORE answering questions about a specific tour — never give generic opinions or advice without consulting the real data first.

Search or fetch posts from the MetaMask Embedded Wallets community forum (builder.metamask.io). Use for troubleshooting real user issues, finding workarounds, and checking if an issue is known. Provide a query to search or a topic_id to read the full discussion.

To help a user register or purchase, call get_activity_details after this — it returns session-level "share_url" links that go directly to checkout. Search children's enrichment activities (camps, classes, after-school programs) by location, age range, date, or keyword. Returns a paginated list with listing-page "url" fields; use slug or id to fetch full details.

Get full details for a specific product by SKU or title. Use when the user asks about a specific product by name (e.g. 'tell me about MIRA', 'show me the serum'). Do not use for browsing or recommendations — use search_products or skincare_recommend. Returns a widget card with the product details, image, price, and checkout button.

Search Vaadin documentation for relevant information about Vaadin development, components, and best practices. Uses hybrid semantic + keyword search. USE THIS TOOL for questions about: Vaadin components (Button, Grid, Dialog, etc.), TestBench, UI testing, unit testing, integration testing, @BrowserCallable, Binder, DataProvider, validation, styling, theming, security, Push, Collaboration Engine, PWA, production builds, Docker, deployment, performance, and any Vaadin-specific topics. When using this tool, try to deduce the correct development model from context: use "java" for Java-based views, "react" for React-based views, or "common" for both. Use get_full_document with file_paths containing the result's file_path when you need complete context.

Get full details for a specific product by SKU or title. Use when the user asks about a specific product by name (e.g. 'tell me about MIRA', 'show me the serum'). Do not use for browsing or recommendations — use search_products or skincare_recommend. Returns a widget card with the product details, image, price, and checkout button.

Submit feedback about your experience using Partle. Tell us what's confusing, broken, or could be better. Args: feedback: Freeform text describing the issue or suggestion (max 5000 chars).

Get Arcadia workflow guides and reference documentation. Call this before multi-step workflows (opening LP positions, enabling automation, closing positions) or when you need contract addresses, asset manager addresses, or strategy parameters. Topics: overview (addresses + tool catalog), automation (rebalancer/compounder setup), strategies (step-by-step templates), selection (how to evaluate and parameterize strategies).