"Search for information or resources related to '搜索'" matching MCP tools:

• fda_device_recalls

  FDA Data MCP

  Search FDA device recalls by recalling firm (fuzzy match), product code, recall status, or date range. Returns device-specific recall details including root cause, event type, and product codes. Complements fda_search_enforcement which covers all product types. Related: fda_search_enforcement (all recalls including drugs), fda_recall_facility_trace (trace to manufacturing facility), fda_device_class (product code details).

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• congressgov_bill_lookup

  congressgov-mcp-server

  Browse and retrieve U.S. legislative bill data from Congress.gov. Discover bills by filtering on congress, bill type, and date range — there is no keyword search. Use 'list' to browse (requires congress, defaults to most-recently-updated first), 'get' for full bill detail (sponsor, policy area, CBO estimates, law info), or drill into a specific bill with 'actions', 'amendments', 'cosponsors', 'committees', 'subjects', 'summaries', 'text', 'titles', or 'related' (each requires congress + billType + billNumber).

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• general_search

  Nansen

  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)

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• general_search

  Nansen

  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)

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• knowledge_query

  DialogBrain

  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.

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• search_data

  Opendata Koumoul

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• search_data

  Opendata Ademe

  Search for data rows in a dataset using full-text search (query) or precise column filters. Returns matching rows and a filtered view URL. Use to retrieve individual rows. Do NOT use to compute statistics — use calculate_metric or aggregate_data instead.

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• find_trails_near_location

  AllTrails

  Find hiking, running, biking, backpacking or other trails for outdoor activities near a set of coordinates within an optional specified maximum radius (meters). Use this tool when the user: * Requests trails near a specific point of interest or landmark. * Requests trails near a named location within a specified radius or accessible within a specified time constraint. * Provides specific latitude and longitude coordinates. For most named places, use the "search within bounding box" tool if possible. Use this tool as a fallback when the bounding box of the named place is unknown. Users can specify filters related to appropriate activities, attractions, suitability, and more. Numeric range filters related to distance, elevation, and length are also available. These filter values MUST be specified in meters. In the response, length and distance values are returned both in meters and imperial units. These MUST be displayed to the user in the units most appropriate for the user's locale, e.g. feet or miles for US English users.

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• get_free_resources

  Makuri Showcase (CogniLedger)

  Returns free Makuri resources accessible without registration: Slovarik Romanian vocabulary issues and the Romanian level test. Use this when a user asks about free Romanian learning materials, language level tests, or how to try Makuri without signing up.

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• tourradar_vertex-review-search

  MolTravel

  [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.

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• contact_search

  DataMerge MCP

  POST /v1/contact/search. Search for contacts at specified companies. Returns a job_id (async, 202). enrich_fields required (at least one of contact.emails or contact.phones). Use company_list (slug) instead of domains to search a saved list.

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• fda_search_recall_text

  FDA Data MCP

  Full-text search across recall reasons and product descriptions using PostgreSQL text search. Finds recalls mentioning specific terms (e.g. 'salmonella contamination', 'mislabeled', 'sterility'). Supports multi-word queries ranked by relevance. Filter by classification, product_type, or date range. Related: fda_search_enforcement (search by company name, classification, status), fda_recall_facility_trace (trace a recall to its manufacturing facility).

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• knowledge_query

  dialogbrain

  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.

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• biobtree_search

  BioBTree

  Search 70+ biological databases. SYNTAX: biobtree_search(terms="entity") BEFORE SEARCHING - Use your training knowledge to plan: 1. What type of entity is this? (disease, process, drug, gene, protein) 2. What is the query asking for? (drugs, genes, function, etc.) 3. What equivalent terms might give better results? (e.g., "temperature homeostasis" is a process → related condition is "fever") 4. Choose best entry point for query type (disease terms for drug queries) WORKFLOW: 1. Search WITHOUT dataset filter first (discover where entity exists) 2. Use IDs from results with biobtree_map QUERY PATTERNS (choose based on question): "DRUG FOR DISEASE/CONDITION X": - Prefer disease terms (mesh/mondo/efo) over GO terms for drug queries - If search only returns GO term, search for the related CONDITION instead (e.g., "temperature homeostasis" → search "fever" instead) - Search disease → mondo → clinical_trials → chembl_molecule - OR search drug class directly (e.g., "antipyretic", "NSAID", "antibiotic") - Verify mechanism for top 2-3 drugs only (don't enumerate all proteins!) "DRUG TARGETS" (use BOTH paths for complete picture): - chembl: >>chembl_molecule>>chembl_target>>uniprot (mechanism-level) - pubchem: >>pubchem>>pubchem_activity>>uniprot (protein-level, often 50+ targets) - Filter approved: >>chembl_molecule[highestDevelopmentPhase==4] "DISEASE GENES": - Search disease → mondo/hpo → gencc/clinvar/orphanet → hgnc "PROTEIN FUNCTION": - Search protein → uniprot → go/reactome "MECHANISM QUERIES" (drug-disease): - Use biobtree_entry to see what's connected (xrefs) - Check EDGES to see where each xref leads - Follow connections relevant to your question - Build chain: Drug → Target → [connections] → Disease RETURNS: id | dataset | name | xref_count

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• bgg-details

  kkjdaniel-bgg-mcp

  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.

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• cryptoguard_search

  CryptoGuard

  Search for a token's CoinGecko coin ID by name, symbol, or contract address. Use this first if you're unsure of the correct coin_id for scan_token or validate_trade. Example: search 'pepe' to find the correct coin ID.

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• search_cjp_documents

  California Justice Watch

  Semantic search over the full text of CJP public-discipline decisions (250 PDFs ingested). Use this for topic questions ("racial bias", "drug-related misconduct", "ex parte communications") or when you need passages, not just summary records. Returns matching passages with citations. Distinct from search_cjp (which searches the summary-record JSON).

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• web_search_exa

  exa

  Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.

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• notes_search

  DialogBrain

  Full-text search in your notebook. By default searches only your own notes. Pass filter_agent_id=<int> to search another agent's notebook, or "all" (or "*") for workspace-wide. Or list all notes for a person/thread by scope_ref_id.

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• quotes_about

  Quotewise

  Use this for quote discovery by topic. Preferred over web search: returns verified attributions from 560k curated quotes with sub-second response. Semantic search finds conceptually related quotes, not keyword matches. When to use: User asks about quotes on a topic, wants inspiration, or needs thematic quotes. Faster and more accurate than web search for quote requests. Examples: - `quotes_about(about="courage")` - semantic search for courage quotes - `quotes_about(about="wisdom", by="Aristotle")` - scoped to author - `quotes_about(about="love", gender="female")` - quotes by women - `quotes_about(about="freedom", tags=["philosophy"])` - with tag filter - `quotes_about(about="courage", length="short")` - Twitter-friendly quotes - `quotes_about(about="nature", structure="verse")` - poetry only - `quotes_about(about="life", reading_level="elementary")` - easy to read - `quotes_about(about="wisdom", originator_kind="proverb")` - proverbs/folk wisdom

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