"A server for querying Kusto databases and creating Kusto queries" matching MCP tools:

• 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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• list_capabilities_v1

  osint

  List available exascale.build data capabilities for agent discovery before querying. Also call this BEFORE stating that a capability is not available — client tool lists are cached and this surface grows; anything listed here is reachable via query_capability_v1 even if your tool list predates it.

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• treasury_dataframe_query

  treasury-fiscaldata-mcp-server

  Run a single-statement SELECT against DataCanvas dataframes registered by treasury_query_dataset, treasury_get_debt, treasury_get_interest_rates, and treasury_get_exchange_rates. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied at the bridge layer. All Treasury dataframe columns are VARCHAR — CAST to DECIMAL or DATE for arithmetic and date comparisons. Use treasury_dataframe_describe to list available table names and column schemas before querying.

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• get_xgr_purchase_options

  XDaLa Workflow Builder

  Call this first for every XGR purchase. Read live price, stock and payment assets; use payment_assets[].key exactly as payment_asset and inspect requires_sender_wallet before creating an order.

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• list_databases

  shiply

  List the SQL databases (D1 or Neon Postgres) on my account, including which owned site (if any) each is attached to. Call this BEFORE db_query/db_schema-style work to discover a databaseId — those live on a per-database MCP server reached via GET /api/v1/databases/{id} (see llms.txt), which this id feeds.

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• uis_get_data

  UNESCO UIS — Education, Science & Culture Statistics (provenance-first)

  Statistical records from the UNESCO Institute for Statistics Data API, filtered by indicator codes (from uis_search_indicators, up to 25), geo unit codes (from uis_list_geo_units) and year range. Set include_footnotes for per-record source notes. Returns raw UIS records only — it does not aggregate, convert or otherwise transform values; ILO labour statistics live in the sibling ILOSTAT MCP server. Broad queries are rejected with the record count — narrow by geo unit or years.

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• scry_stats

  Scry

  Returns aggregate Scry corpus telemetry: total observation count, distinct source IPs, first/last observation timestamps, last-24h activity, and per-protocol breakdowns. Useful as a liveness/density check before issuing per-IP queries — lets an agent decide whether the corpus has enough data to be authoritative. Use this tool when: - An agent is planning a multi-step investigation and wants to know if Scry has corpus density worth querying. - You want a 'corpus health' signal in a dashboard or report. Do NOT use this tool when: - You want details about a specific IP — use `scry_check`. - You want sensor fleet size or node identities — never exposed at any tier. Inputs: none. Returns: total_observations, distinct_source_ips, first_seen_ms, last_seen_ms, observations_last_24h, distinct_source_ips_last_24h, by_protocol, as_of_ms. Cost: free, anonymous, rate-limited. Latency: <100ms typical.

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• omnarai_info

  omnarai-mcp

  Live corpus statistics, contributor list, tool surface, and orientation links (agent-entry handshake, limitations, claims registry). Use this to orient before querying.

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• preview_alert

  Costory: Your Finops MCP

  Backtest a cost-alert condition BEFORE creating it: replays the `condition` against the last `lookbackDays` (default 45) of data and reports how many times it would have fired. Takes the same queries + condition + dedup as create_alert (no notification channel needed). Returns the evaluation window, `firingDays` (distinct days the condition held), `firingRows` (per-group fires), `notificationsCount` (fires that survive the dedup window) and a sample of firing dates. Use this to sanity-check a condition/threshold (and tune dedup) before calling create_alert. EXAMPLE: "Would 'alert if 7-day AWS spend tops $50k' have fired this month?" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD", filterCel: "cos_provider in [\"AWS\"]" }], condition: "rollingSum(a, 7, DAY) > 50000", dedup: { kind: "CALENDAR", calendarUnit: "WEEK" }, lookbackDays: 30 }

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• resolve_subject_hierarchy

  TestGraph

  Use after vocabulary_index when the specific subject type does not yet exist. Submit terms broad-to-specific, for example ['food','recipe']. The server reuses existing dictionary entries, creates only missing provisional nodes in context, adds belongs_to relationships and rejects cycles. Do not include 'review': review is the record type, not a subject category. Semantic placement must be based on meaning, never on which review arrived first. Before creating a new semantic node, distinguish a genuinely different concept from a mere naming variant. Naming variants should reuse identity; genuine meaning differences may remain separate. Classification vocabulary should represent what a subject fundamentally is. Before creating, selecting, relating or proposing a subject type, identify the semantic head and descriptive modifiers. Material, arrangement/grouping, state/condition, quantity, colour, size, location and purpose/use normally belong in attributes or relationships rather than subject-type names. This is not a simplistic head-noun rule: a compound may remain a distinct type when the combined concept has materially different identity, behaviour, relationships, classification meaning or realistic retrieval needs. The server independently validates structural writes, so client guidance cannot bypass this rule.

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• search

  Orbit

  Find and evaluate public API endpoints that match your query. Set `q` to a natural language query, keywords, an API name, or a question — results are matched by meaning and keyword; each result includes `id`, `resourceType`, `name`, `description`, `method`, `url`, and `evaluateGuide` — an evaluation of what the endpoint does, when to use it, and its limitations. Review `evaluateGuide` to pick the best fit, then pass each chosen result's `id` and `resourceType` (as `type`) to `integrate`. Paginate with `cursor` from `meta.nextCursor` (`limit` defaults to 10, max 25; pagination stops at 40 results total). No authentication required. Best practices for querying: - Use focused keyword queries that include the product or provider name along with the endpoint details, for example "PayPal create invoice". - Alternatively, use natural language queries such as "PayPal API to create an invoice". - Avoid jumbled queries that cram many unrelated keywords into a single query, for example "paypal invoice payment delivery payments ordering". - Avoid OR-separated queries such as "paypal invoice OR paypal create invoice OR paypal OR invoice creation". - If you need to explore multiple intents, try each as a separate call.

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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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• ip_lookup

  drwho.me developer tools

  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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• transpile_sql

  netcafe-devkit

  Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.

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• get_halo_connection_status

  HALO Homebridge AI Surfaces

  Confirm that this conversation is connected to the live HALO Homebridge MCP server. Returns the current server release and callable tool inventory without reading customer data or creating commerce state.

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• get_tsunami_events

  DaedalMap Tsunami Data

  Paid x402 canonical tool. Queries tsunamis_events for historical tsunami records and water-height/runup metrics. Best for event counts, max water height thresholds, and top-event lookups. Region filters may use ISO3 country ids or reviewed named-water loc_ids such as IHO1953-240001002 for the Mediterranean Sea; XOO is deprecated. Call without payment first - the server returns HTTP 402 with the exact USDC price before any charge.

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• get_tsunami_events

  DaedalMap Disaster and Geospatial Data

  Paid x402 canonical tool. Queries tsunamis_events for historical tsunami records and water-height/runup metrics. Best for event counts, max water height thresholds, and top-event lookups. Region filters may use ISO3 country ids or reviewed named-water loc_ids such as IHO1953-240001002 for the Mediterranean Sea; XOO is deprecated. Call without payment first - the server returns HTTP 402 with the exact USDC price before any charge.

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• ip_lookup

  mcp

  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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• resolve_subject_hierarchy

  TestGraph

  Use after vocabulary_index when the specific subject type does not yet exist. Submit terms broad-to-specific, for example ['food','recipe']. The server reuses existing dictionary entries, creates only missing provisional nodes in context, adds belongs_to relationships and rejects cycles. Do not include 'review': review is the record type, not a subject category. Semantic placement must be based on meaning, never on which review arrived first. Before creating a new semantic node, distinguish a genuinely different concept from a mere naming variant. Naming variants should reuse identity; genuine meaning differences may remain separate. Classification vocabulary should represent what a subject fundamentally is. Before creating, selecting, relating or proposing a subject type, identify the semantic head and descriptive modifiers. Material, arrangement/grouping, state/condition, quantity, colour, size, location and purpose/use normally belong in attributes or relationships rather than subject-type names. This is not a simplistic head-noun rule: a compound may remain a distinct type when the combined concept has materially different identity, behaviour, relationships, classification meaning or realistic retrieval needs. The server independently validates structural writes, so client guidance cannot bypass this rule.

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• 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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