134,441 tools. Last updated 2026-05-23 17:11
"A server for exploring information about quantum physics or quantum-related topics" matching MCP tools:
- Get a snapshot of the quantum computing landscape — no parameters needed. Use when the user asks broad questions like "how's the quantum job market?", "what are trending topics?", or wants an overview of the quantum computing industry. Returns: total active jobs, top hiring companies, jobs by role type, papers published this week, total researchers tracked, and trending technology tags. For specific job/paper/researcher searches, use the dedicated search tools instead.Connector
- 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".Connector
- Create multiple nodes at once (up to 500 per call). Uses Neo4j UNWIND for high performance. Essential for knowledge graph population — create hundreds of entities from a single book chapter or article. Each node needs: entity_id (unique string) and data (properties dict). Example: entity_type: "concept" nodes: [ {"entity_id": "quantum-mechanics-001", "data": {"name": "Quantum Mechanics", "field": "Physics"}}, {"entity_id": "wave-function-001", "data": {"name": "Wave Function", "field": "Physics"}}, {"entity_id": "superposition-001", "data": {"name": "Superposition", "field": "Physics"}} ]Connector
- Quantum Wallet Generation: Generate BIP-39 mnemonic seed phrases from real ANU quantum entropy (vacuum fluctuation measurements). Returns 12 or 24-word mnemonics with derived addresses for EVM, Solana, and Bitcoin.Connector
- Quantum Portfolio Risk Monitor: Scan multiple wallet addresses across chains for quantum vulnerability. Aggregates risk scores, identifies value at risk, and provides portfolio-level quantum threat assessment with risk distribution.Connector
- Quantum Signing Key Generator: Generate Ed25519 or secp256k1 signing keypairs from real ANU quantum entropy. Returns private key and public key pair.Connector
Matching MCP Servers
- Alicense-qualityCmaintenanceAn MCP server that provides static validation and documentation lookup for quantum computing libraries, currently supporting PennyLane. It allows users to verify quantum code syntax and method usage against official library documentation to ensure correct implementation.Last updatedMIT
- Alicense-qualityBmaintenanceEnables AI assistants to perform quantum-resistant cryptographic operations using NIST-standardized algorithms including ML-KEM, ML-DSA, and SPHINCS+. Supports key generation, encryption, digital signatures, and security analysis for post-quantum cryptography research and development.Last updated1MIT
Matching MCP Connectors
QuantumOracle — 18 post-quantum crypto tools: Kyber, Dilithium, hybrid schemes, migration.
AI triage for quantum computing POC proposals. Screens before budget is allocated.
- Hardware-Verified Quantum Random Number Generator: Generate cryptographically secure random numbers on real IBM quantum hardware (127-qubit superconducting processor). Each result includes IBM job ID as proof of quantum origin.Connector
- Find quantum computing researchers and potential collaborators from 1000+ active profiles. Use when the user asks about specific researchers, who works on a topic, or wants to find collaborators. NOT for jobs (use searchJobs) or papers (use searchPapers). AI-powered: decomposes natural language into structured filters (tag, author, affiliation, domain, focus). Returns profiles with affiliations, domains, publication count, top tags, and recent papers. Data from arXiv papers published in the last 12 months. Max 50 results. Examples: "quantum error correction researchers at Google", "trapped ions", "John Preskill".Connector
- Returns information about safety features on Makuri, including age verification, content filtering, parental controls, and AI safety guardrails. Use when the user asks about child safety, content moderation, or how Makuri protects minors.Connector
- 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
- Get full details for a specific quantum computing job by its numeric ID. Use after searchJobs when the user wants more information about a specific position. Returns: job summary, required skills, nice-to-have skills, responsibilities, visa sponsorship, salary, location, and apply URL. Requires a valid job_id from searchJobs results. Returns error if ID not found.Connector
- Get today's quantum computing papers from arXiv — no parameters needed. Use when the user asks "what's new in quantum computing?" or wants a daily paper briefing. Returns the most recent day's papers with title, authors, date, AI-generated hook (one-line summary), and tags. For date-range or topic-filtered search, use searchPapers instead. Use getPaperDetails for full abstract and analysis of a specific paper.Connector
- Get full details for a specific quantum computing paper by its arXiv ID (e.g., "2401.12345"). Use after searchPapers or getLatestPapers when the user wants to dive deep into a specific paper. Returns: complete abstract, all authors, publication date, AI-generated tags with reasons, hook (one-line summary), methodology, gist, and key findings. Requires a valid paper_id from search results. Returns error if not found.Connector
- 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
- 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)Connector
- 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)Connector
- Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.Connector
- BROWSING / DISCOVERY search — cities, neighbourhoods, or mixed venues near a location. Use this when the user is exploring a REGION rather than looking for a specific category. Supports population filtering ('cities > 100k'), distance/population sorting, and layer filtering (locality / neighbourhood / venue / address / street). For specific POI categories (gas, food, charging, etc.), use `search_places` instead.Connector
- Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.Connector
- Search across ALL string properties of ALL nodes in a deployed graph using free-text queries. Unlike search_graph_nodes (which filters by specific property), this searches every text field at once. Perfect for finding knowledge when you don't know which property contains the answer. Example: query "quantum" searches name, description, summary, notes, and all other string fields. Returns nodes with _match_fields showing which properties matched. Optionally filter by entity_type to narrow results.Connector