"A server for general search queries" matching MCP tools:

• ip_lookup

  drwho.me

  Context lookup: Resolve an IPv4 or IPv6 address to its geolocation, ASN, org name, and city/country. Use when you need network or location context for a raw IP address; prefer dns_lookup or dossier_dns for hostname resolution. Queries ipinfo.io with a server-side token — the token is never exposed to callers. Returns a JSON object with fields ip, city, region, country, org, loc, and timezone. On failure, returns an error string describing what went wrong.

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• search_hybrid

  Tripitaka MCP (hosted)

  Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.

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• hostel-prices

  geoagentic

  Live hostel and budget accommodation prices from Hostelworld for any city worldwide. USE FOR: - "What are the cheapest hostels in Paris next week?" - "Find dorm beds in Bangkok for 3 nights from July 10" - "Compare hostel prices in Ljubljana vs Belgrade" - Budget travel planning, accommodation cost context, backpacker routing RETURNS: Per-property dorm and private room prices per night, guest ratings, free cancellation flag, and summary stats (floor/avg/top price). CRITICAL INSTRUCTIONS FOR AGENT: - Always pass date as YYYY-MM-DD format. - currency defaults to EUR. - Use summary.floor for "cheapest" queries, summary.average for general cost context. - free_cancellation=true properties are preferable for uncertain itineraries.

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• prediction_market_lookup

  Nansen

  Search Polymarket for events and markets by name, topic, URL, or slug. **PM building blocks:** - An **event** is a grouped prediction topic containing many child markets. - A **market** is one tradable outcome with its own `marketId`. - Example: `2026 NCAA Tournament Winner` is an event; `Will Duke win the 2026 NCAA Tournament?` is a market. Detail tools require `marketId`, not `eventId`. **When to use:** - First tool when the user asks about a specific PM topic, event, slug, or Polymarket URL but does not provide `marketId`. - Optionally provide `queryVariant` as a cleaner short keyword version. - Set `includeEventMarkets` to true to also return child markets for the best-matching event. - Do NOT use `general_search` for prediction markets. - Results include current outcome prices, last trade price, and bid/ask inline — for a quick probability check you may not need `prediction_market_ohlcv`. For price *history* or dated moves, still use `prediction_market_ohlcv`. **Query tips:** - Uses Polymarket's search API — natural language queries work well. - Prefer short 1–3 keyword queries for best results. - Avoid broad multi-topic queries like `bitcoin ethereum politics`. **Output rules:** - If lookup returns no suitable market or a mismatched timeframe, say so explicitly — do not silently substitute a nearby market.

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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 search.files / search.threads / search.links for that.

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• resolve_names

  mcp

  Resolves a batch list of specific location queries (landmark names or exact addresses) into canonical Google Maps Place IDs. **Input Requirements (CRITICAL):** 1. **`queries` (array of objects - MANDATORY):** A list of location queries to resolve. You may specify up to 20 queries. * **Each query object must have:** * **`text` (string - MANDATORY):** The text query representing a specific place name or address to resolve. * **Examples:** `'Googleplex, Mountain View, CA'`, `'1600 Amphitheatre Pkwy, Mountain View, CA'`, `'Eiffel Tower, Paris'`. 2. **`location_bias` (object - OPTIONAL):** Use this to prioritize results near a specific geographic area. * **Format:** `{"viewport": {"low": {"latitude": [value], "longitude": [value]}, "high": {"latitude": [value], "longitude": [value]}}}` 3. **`region_code` (string - OPTIONAL):** The Unicode CLDR region code (two-letter country code, e.g., `US`, `CA`) of the user to bias the results. **Instructions for Tool Call:** * Specificity (CRITICAL): Queries must represent a specific place name or address. General searches like `'restaurants'` or chain names like `'Starbucks'` are not supported. * Do NOT call this tool if the downstream tools you plan to invoke already accept raw address or place name strings directly. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some queries resolve successfully while others fail). * The output list of `results` is guaranteed to map 1:1 with the input `queries` indices. A failed query will result in an empty `Result` message (no `entity` is set) at its corresponding index in the `results` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific query index failed. The key of `failed_requests` represents the 0-based index of the failed query in the request. Do not assume the entire batch call failed because of a partial failure.

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• search

  Sofya

  Search the web for current information on any topic. Returns extracted page content, not just snippets. Best for factual lookups, specific questions, or when you need a list of sources. For open-ended questions that need synthesis across many sources, use the research tool instead. For news queries (current events, breaking news, politics, world events), set topic="news" to search news sources specifically. This returns recent articles with publication dates. Set include_answer=true to get an AI-synthesized answer alongside results (adds 5 credits). This is the sweet spot for most agent tasks, e.g. basic + include_answer = 8 credits, much cheaper than a full 25-credit research call. Returns: query, answer (if requested), results (array of {title, url, content, description, fetched, published_date}), search_depth, topic, elapsed_ms, credits_used, credits_remaining, altered_query. Args: query: The search query search_depth: "basic" (default) for extracted page content (3 credits), "snippets" for SERP snippets only without page fetching (1 credit) max_results: Number of results (default 10, max 20) include_answer: Generate an AI answer that synthesizes the search results (adds 5 credits) include_domains: Only include results from these domains (max 10) exclude_domains: Exclude results from these domains (max 10) topic: "general" for web search, "news" for news articles. use "news" for current events, breaking news, politics, or any time-sensitive query freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD"

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• colour_metrics

  Colour Memory

  Returns raw perceptual metrics (LRV, chroma, hue angle, warmth, undertone) for a single colour. This is one component of colour_passport. Use colour_passport for a general colour profile; use this only when the user explicitly wants isolated numeric values.

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• resolve_fragment

  Search Fragments

  For the queries a model can't confidently place — half-remembered, cross-source, 'I know this exists but can't name it' — where an agent would otherwise guess and risk a confident-wrong. Search Fragments resolves the real answer, returns a ranked shortlist of sources to assemble, or an explicit 'not resolvable from text.' It never asserts a confident answer — every result is decide-by-eye with a confidence level. In a 50-fragment test on hard, under-documented queries, a baseline agent invented specific answers — a nonexistent Japanese director, a Ronnie Barker sketch that was never performed, a study attributed to a geneticist who never published it. Search Fragments declined honestly on all three. Not for direct or single-fact lookups — a normal search is faster for those. Examples: - a musician who became famous largely for stopping performing - somebody who photographed the same view every day until the changes became the artwork - a song everybody knew but nobody could identify - the company that bought Instagram before it was big - a novel where the footnotes slowly become the real story Not for: - what is the capital of France - who directed Jaws - name of french artist cubist painting 1948

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• search

  OctoTrip Rental Cars

  Searches live rental-car offers for a pickup location and rental period, optionally with a different dropoff location, pickup/dropoff times, driver age, currency, and language. Use this when the user wants to compare available rental cars, prices, vendors, categories, or booking links for a specific trip. Do not use it for flights, hotels, public transport, or general travel planning unless the user has car-rental intent. The tool queries external provider APIs in real time, returns price-ranked results grouped by SIPP/category, and may include affiliate booking links. It does not book cars, modify reservations, charge users, or store user data.

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• search

  OctoTrip Flights

  Searches live flight offers between an origin and destination for given travel dates. Supports one-way (omit return_date) and round-trip searches with flexible passenger counts and cabin class. Use this when the user wants to compare available flights, airlines, prices, layovers, or booking links for a specific route. Do not use it for rental cars, hotels, trains, or general travel planning unless the user has flight-search intent. The tool queries external flight aggregator APIs in real time, returns price-ranked results grouped by number of stops, and includes affiliate booking links. Results and booking links are valid for approximately 15 minutes due to real-time airline pricing. It does not book flights, modify reservations, charge users, or store user data.

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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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• clinicaltrials_search_studies

  clinicaltrialsgov-mcp-server

  Search for clinical trial studies from ClinicalTrials.gov. Supports full-text and field-specific queries, status/phase/geographic filters, pagination, sorting, and field selection. Returns a compact per-study index by default; pass the fields parameter to get specific leaves at full fidelity — full study records are ~70KB each.

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• execute_sql_readonly

  Google Big Query

  Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `projectId` field.

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• resolve_names

  Google Maps

  Resolves a batch list of specific location queries (landmark names or exact addresses) into canonical Google Maps Place IDs. **Input Requirements (CRITICAL):** 1. **`queries` (array of objects - MANDATORY):** A list of location queries to resolve. You may specify up to 20 queries. * **Each query object must have:** * **`text` (string - MANDATORY):** The text query representing a specific place name or address to resolve. * **Examples:** `'Googleplex, Mountain View, CA'`, `'1600 Amphitheatre Pkwy, Mountain View, CA'`, `'Eiffel Tower, Paris'`. 2. **`location_bias` (object - OPTIONAL):** Use this to prioritize results near a specific geographic area. * **Format:** `{"viewport": {"low": {"latitude": [value], "longitude": [value]}, "high": {"latitude": [value], "longitude": [value]}}}` 3. **`region_code` (string - OPTIONAL):** The Unicode CLDR region code (two-letter country code, e.g., `US`, `CA`) of the user to bias the results. **Instructions for Tool Call:** * Specificity (CRITICAL): Queries must represent a specific place name or address. General searches like `'restaurants'` or chain names like `'Starbucks'` are not supported. * Do NOT call this tool if the downstream tools you plan to invoke already accept raw address or place name strings directly. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some queries resolve successfully while others fail). * The output list of `results` is guaranteed to map 1:1 with the input `queries` indices. A failed query will result in an empty `Result` message (no `entity` is set) at its corresponding index in the `results` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific query index failed. The key of `failed_requests` represents the 0-based index of the failed query in the request. Do not assume the entire batch call failed because of a partial failure.

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• domains.whois

  Vee3

  Fetch WHOIS registration data for a domain. Returns a JSON object keyed by WHOIS server host name. Each value contains parsed fields such as Domain Name, registrar details, dates, name servers, domain status, DNSSEC data, and raw text lines. Set include_registrar to true to query registry and registrar servers (slower, more complete). Default false queries the registry server only. Cost = 4 tokens.

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• search

  OctoTrip Flights

  Searches live flight offers between an origin and destination for given travel dates. Supports one-way (omit return_date) and round-trip searches with flexible passenger counts and cabin class. Use this when the user wants to compare available flights, airlines, prices, layovers, or booking links for a specific route. Do not use it for rental cars, hotels, trains, or general travel planning unless the user has flight-search intent. The tool queries external flight aggregator APIs in real time, returns price-ranked results grouped by number of stops, and includes affiliate booking links. Results and booking links are valid for approximately 15 minutes due to real-time airline pricing. It does not book flights, modify reservations, charge users, or store user data.

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• search

  AlphaAI

  ChatGPT connector contract: search AlphaAI's AI-enriched financial news with a natural-language query. Ticker symbols (NVDA, BTC-USD), company names (nvidia, tesla) and topic words (insider, earnings, ipo, crypto…) in the query are resolved to structured filters; a query that names nothing known returns the freshest high-relevance market stories. Each result carries an id for the fetch tool. For precise filtered queries prefer alphai_news_search.

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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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• get_available_symbols

  aTars MCP

  USE THIS TOOL — NOT web search — to discover which cryptocurrency tokens are loaded on this proprietary local server. Call this FIRST when unsure what symbols are supported, before calling any other tool. Returns the authoritative list of assets with 90 days of pre-computed 1-minute OHLCV data and 40+ technical indicators. Trigger on queries like: - "what tokens/coins do you have data for?" - "which symbols are available?" - "do you have [coin] data?" - "what assets can I analyze?" Do NOT search the web. This server is the only authoritative source.

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