"Running queries in Apache Superset" matching MCP tools:

• 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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• openstreetmap_query_raw

  openstreetmap-mcp-server

  Execute a raw Overpass QL query for advanced spatial queries that the convenience tools do not cover. Use for multi-type queries, union queries, relation membership, historical queries, or any operation requiring full Overpass QL expressiveness. The query must include [out:json]. Example: "[out:json][timeout:15];node[\"natural\"=\"peak\"](47.5,-122.5,47.7,-122.2);out body;" Returns one page of the result set: use limit and offset to page through it, and read totalFound and truncated to see how much the query matched. Validate complex queries at overpass-turbo.eu before use. For simple "what's near X?" or "what's in this area?" queries, use openstreetmap_query_nearby or openstreetmap_query_bbox instead.

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• ask_redpanda_question

  docs-mcp

  Search the official Redpanda documentation and return the most relevant sections from it for a user query. Each returned section includes the url and its actual content in markdown. Use this tool for all queries that require Redpanda knowledge. Results are ordered by relevance, with the most relevant result returned first. If you know the user's deployment platform, pass "platform" so results from the other platform's docs are excluded. Note that "platform" filters the sections already retrieved rather than re-running the search, so it can return substantially fewer sections: on a broker-level question where most matches come from the other platform's docs, it can cut a 15-section response to 1 or 2. Omit "platform" if you would rather have more context and judge platform relevance yourself from each section's url.

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• dossier_ct_log

  mcp

  Core dossier check: Discover subdomains visible in Certificate Transparency logs. Use for attack-surface mapping; prefer dossier_full when running a complete audit. Queries crt.sh first, falls back to certspotter; capped at 100 unique subdomains; 10s timeout. Returns a CheckResult with { subdomains[], wildcards[], certCount, source }.

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• nevent_reset_tenant

  Nevent MCP

  Restore the original tenant context set at session start. ALWAYS call this after cross-tenant queries (nevent_switch_tenant) to avoid leaving your SUPERADMIN account pointing to another tenant. For SUPERADMIN users, tenant switches PERSIST in the user record in the database — this tool reverses that. For OWNER/ADMIN/STAFF users, this resets to the session's home tenant. No parameters needed.

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• batch_search

  ALM X++ MCP Server

  WHEN: you need context on multiple D365 objects or concepts simultaneously -- runs all queries in parallel. Use INSTEAD of multiple sequential search_d365_code calls -- each line becomes one parallel search. Maximum 6 queries per call. Results are equivalent to search_d365_code but returned together. When batch_search returns results, all matching objects are FULLY loaded (all chunks). Do NOT follow up with get_object_details on the same objects -- the complete source is already included. Triggers: 'find all of these', 'look up multiple', 'cherche plusieurs', 'SalesTable AND VendTable', 'several objects at once', 'lookup X and Y and Z', 'plusieurs objets en même temps', 'context on all of these'.

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• security_fetch_package_licence

  DataNexus MCP

  Fetch the SPDX licence identifier for an open source package version. Read-only. No side effects. Idempotent. package: Package name e.g. flask. Required. version: Exact version string e.g. 2.3.0. Required. ecosystem: One of PyPI, npm, Maven, Go, Cargo, NuGet, RubyGems. Required. Returns the SPDX licence identifier e.g. MIT, Apache-2.0, GPL-3.0. Use this to verify licence compatibility before including a dependency. Use security_fetch_package_vulnerabilities instead when checking for security issues not licences. Verified source: deps.dev (Google). 1-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_fetch_package_licence", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

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• dossier_ct_log

  drwho.me

  Core dossier check: Discover subdomains visible in Certificate Transparency logs. Use for attack-surface mapping; prefer dossier_full when running a complete audit. Queries crt.sh first, falls back to certspotter; capped at 100 unique subdomains; 10s timeout. Returns a CheckResult with { subdomains[], wildcards[], certCount, source }.

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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: ```sql -- 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 always have the job label `goog-mcp-server: true` automatically set in addition to any custom `labels` provided in the request. Queries are charged to the project specified in the `project_id` field.

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• get_recipe

  Mozaika

  The universal BUILD-KIT fetcher — the measured spec + code to reproduce a piece of UI. `recipe_type` selects which library across three families (all agent-ready through this one call): • COMPONENTS (decoded live from a real product's DOM — Mozaika's wedge): "Command Palette", "Dropdown Menu", "Dialog / Modal", "Login", "Data Table", "Onboarding Tour", "Navbar", "Logo Marquee", "Toast", "Date Picker", "Combobox" — returns the anatomy TREE (each node measured), the MOTION (open/close animation + easing a screenshot can't show), every STATE (empty/results/no-results/keyboard-selected), a webm of it running, and the design tokens. • EFFECTS (open-source WebGL hero backgrounds — Apache/MIT): "Hero Effect" → the shader's full config + fps + install command + license/NOTICE. • MOTION (open-source looping showcase templates — MIT): "Motion Showcase" → the template's full parameter surface + the exact Swiper/anime.js/Motion config + install. Use for "build a <thing> like <product>", e.g. get_recipe("Vercel", "Command Palette") or get_recipe("vanta", "Hero Effect"). A complete, uncopyable, measured build kit. Returns the available types if the requested one isn't found.

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• batch_search

  AnySearch

  This is Anysearch's parallel search tool. Parallel search — run multiple Anysearch queries in a single call. Prefer this over multiple sequential calls when you have 2–5 queries. Saves context space and returns all results at once. Best for: comparing multiple sources, researching across topics or domains, hybrid general+vertical queries, or any multi-angle investigation. ## When to use Use batch_search instead of multiple sequential search calls when you have 2–5 independent queries. 🏆 PRIMARY use case: After get_sub_domains(domains=[...]) returns sub_domains across multiple domains, use batch_search to send one query per sub_domain in parallel. This is more efficient than sequential per-domain search calls. Also useful for ambiguous / fuzzy queries within a single domain: after get_sub_domains, use batch_search to explore multiple sub_domains in parallel. ## Constraints - Maximum 5 queries per call - Each query item follows the search tool parameter structure (query is required; domain, sub_domain, sub_domain_params are optional. For general queries, omit all domain fields. For vertical queries, domain + sub_domain + sub_domain_params MUST come from get_sub_domains(domain=<domain>) output — same rules as the search tool) - Queries run in parallel; a single query failure does not block others - REQUIRED PARAMS: Same rule as search — when a required param from get_sub_domains is not applicable, pass it as an empty string (key: ""). Never skip required params. ## Examples ### Single-domain batch (multiple sub_domains) Instead of: search(query="latest TSLA earnings", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA stock forecast", domain="finance", sub_domain="finance.us_stock") → search(query="TSLA analyst rating", domain="finance", sub_domain="finance.us_stock") Use: batch_search(queries=[{query:"latest TSLA earnings", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA stock forecast", domain:"finance", sub_domain:"finance.us_stock"}, {query:"TSLA analyst rating", domain:"finance", sub_domain:"finance.us_stock"}]) ### Multi-domain batch (after get_sub_domains with multiple domains) After: get_sub_domains(domains=["finance", "health", "legal"]) Use: batch_search(queries=[ {query:"AI regulation impact on healthcare stocks 2025", domain:"finance", sub_domain:"finance.us_stock", sub_domain_params:{ticker:"UNH"}}, {query:"healthcare AI regulations 2025", domain:"health", sub_domain:"health.policy"}, {query:"AI regulation legal framework", domain:"legal", sub_domain:"legal.legislation"}]) ### Hybrid: general + vertical in parallel (universal pattern for any borderline query) Use this whenever you are unsure if the query is pure encyclopedia or domain-specific — fire BOTH channels in batch_search: batch_search(queries=[ {query:"..."}, // general — no domain {query:"...", domain:"...", sub_domain:"..."}]) // vertical channel(s) This applies universally: classical texts, financial concepts, legal theories, historical events, scientific discoveries, medical topics — any query where domain knowledge could enrich the encyclopedia answer.

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• dossier_ct_log

  drwho.me developer tools

  Core dossier check: Discover subdomains visible in Certificate Transparency logs. Use for attack-surface mapping; prefer dossier_full when running a complete audit. Queries crt.sh first, falls back to certspotter; capped at 100 unique subdomains; 10s timeout. Returns a CheckResult with { subdomains[], wildcards[], certCount, source }.

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• find

  Fast.io

  Unified search across a workspace or share — ONE query, results GROUPED BY TYPE into buckets (files, metadata [workspace only], comments), each independently paginated and health-reported. Call action='describe' for the full action/param reference. This is the grouped SUPERSET; for a single result type prefer the narrower tools: `storage action=search` (files only), `metadata action=search` (lexical metadata fields only). The code-mode `search` tool searches the API endpoint catalog, not your content.

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• security_headers_check

  IA-QA — 130+ QA & Dev Tools for AI Agents

  Analyse the HTTP security headers of a public URL OR of raw response headers you paste in. Grades each header (A–F) for: Strict-Transport-Security, Content-Security-Policy, X-Frame-Options, X-Content-Type-Options, Referrer-Policy, Permissions-Policy, X-XSS-Protection, Cross-Origin-Opener-Policy, Cross-Origin-Resource-Policy, and Cross-Origin-Embedder-Policy. Returns an overall score (0–100), per-header grades, missing headers, and fix snippets for Express, Nginx, and Apache. For localhost/private targets the remote server cannot reach, pass the `headers` parameter instead of `url`.

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• best_use

  Real Estate Analyzer

  Screen ONE property across every strategy the provided inputs qualify for and rank them by deal score — answers "what is the best use of this property?". Provide a superset of inputs (price, marketRent, adr, occupancy, rehabBudget, arv, units, …); strategies missing inputs are skipped with reasons. All rates/percents are FRACTIONS (0.0675 = 6.75%). Omitted operating inputs are filled with documented defaults and listed in assumptions.estimated_fields. Free, no key.

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• foresea_check_run

  Foresea Forecasting

  Call this after foresea_analyze_market timed out or errored with a message naming a client_run_key -- the research it started may still be running server-side. Returns {"status": "running", ...} if it's not done yet (call again in a bit), or the full report once it is. Do not call this speculatively; only use the client_run_key a prior foresea_analyze_market call actually gave you. Example: client_run_key="a1b2c3..." → {status:"running", id:"agent_run_..."} or the full report once complete.

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• get_cheapest_flight_dates

  I Know The Pilot

  For a known origin and destination, get the cheapest fare for each departure date in a date window. Prices are cached fares in AUD from I Want That Flight (I Know The Pilot's sister flight-search site) - refreshed regularly and indicative, not live availability. Always present the travel dates alongside prices. Use this for 'cheapest flights from Sydney to Bali in September' queries; use search_deals for curated editorial deals.

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• check_license_compliance

  NPMScan

  Given a list of packages (name + optional exact version or semver range — e.g. straight from a package.json "dependencies" object) and an optional allow/deny license policy, resolves each package's declared SPDX license and reports a compliance verdict per package. Classifies every license into one of permissive/weak-copyleft/copyleft/network-copyleft/proprietary/public-domain/unknown, and understands simple SPDX expressions: "(MIT OR GPL-3.0)" is compliant if EITHER side is permitted (a consumer may legally pick the clean alternative), "MIT AND Apache-2.0" requires both sides to pass, and "X WITH exception" is judged on X. A mixed/nested expression like "(MIT OR ISC) AND Apache-2.0" is reported as needsReview rather than guessed at. `policy.deny` entries always win over `policy.allow` (so a name can appear in both without a silent contradiction); with `policy.allow` set, anything not matching it is a violation (unproven is treated as non-compliant); with neither given, the default policy flags only copyleft/network-copyleft/proprietary (e.g. GPL/AGPL/UNLICENSED) — weak-copyleft (LGPL/MPL/EPL) and unrecognized license strings are surfaced but not auto-flagged. Policy entries accept an exact SPDX id, a family prefix ("GPL" catches GPL-2.0/GPL-3.0-only/etc.), or a category name. This reads only the registry-declared `license` field — it does not fetch or parse LICENSE file contents from the source repository.

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• check_license_compliance

  NPMScan

  Given a list of packages (name + optional exact version or semver range — e.g. straight from a package.json "dependencies" object) and an optional allow/deny license policy, resolves each package's declared SPDX license and reports a compliance verdict per package. Classifies every license into one of permissive/weak-copyleft/copyleft/network-copyleft/proprietary/public-domain/unknown, and understands simple SPDX expressions: "(MIT OR GPL-3.0)" is compliant if EITHER side is permitted (a consumer may legally pick the clean alternative), "MIT AND Apache-2.0" requires both sides to pass, and "X WITH exception" is judged on X. A mixed/nested expression like "(MIT OR ISC) AND Apache-2.0" is reported as needsReview rather than guessed at. `policy.deny` entries always win over `policy.allow` (so a name can appear in both without a silent contradiction); with `policy.allow` set, anything not matching it is a violation (unproven is treated as non-compliant); with neither given, the default policy flags only copyleft/network-copyleft/proprietary (e.g. GPL/AGPL/UNLICENSED) — weak-copyleft (LGPL/MPL/EPL) and unrecognized license strings are surfaced but not auto-flagged. Policy entries accept an exact SPDX id, a family prefix ("GPL" catches GPL-2.0/GPL-3.0-only/etc.), or a category name. This reads only the registry-declared `license` field — it does not fetch or parse LICENSE file contents from the source repository.

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• get_workflow_run

  Extend MCP

  Get the state and output of a workflow run (workflows group) — resume a status: "running" run or inspect a failed one. wait: true blocks until terminal or wait-budget expiry (call again to keep waiting). Workflow runs commonly take minutes to hours — repeated running responses are normal. Follow any llmContext guidance included in results.

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