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

• strale_ping

  Strale - 290+ API capabilities for AI agents

  Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.

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• switch_dannet_server

  dannet

  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")

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• kochava_free_app_analytics_get_tos

  Kochava for Advertisers — Official MCP Server

  Retrieve the FAA (Free App Analytics) Terms of Service document link. Use this tool when the user wants to review the Terms of Service before creating an FAA account. Returns a clickable link to the TOS document and instructions for account creation. Example: kochava_free_app_analytics_get_tos()

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• get_api_key_instructions

  Kamy

  Returns step-by-step instructions for creating a Kamy API key in the dashboard. Does not open the browser.

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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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• describe_schema

  Valuein — SEC EDGAR Fundamentals

  Returns the Parquet schema for all tables in the Valuein SEC data warehouse. Includes table descriptions, column names, types, primary keys, and foreign-key references. Use this tool to understand the data model before querying with other tools. No data reads required — schema is embedded in the manifest. Available on all plans.

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• get_guide

  Canvs

  ⚠️ MANDATORY FIRST STEP - Call this tool BEFORE using any other Canvs tools! Returns comprehensive instructions for creating whiteboards: tool selection strategy, iterative workflow, and examples. Following these instructions ensures correct diagrams.

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• vf_health

  VoiceFlip

  Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.

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• suggest_entity

  connect

  Search for existing entities (people, galleries, museums, auction houses, institutions, foundations, collectors) by name. Use this before creating a new entity to check for duplicates — the system includes ~2,500 major galleries, museums, and auction houses. Returns matching entities for autocomplete-or-create flow. If no match is found, create a new entity via create_entity.

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• get_knowledge_stats

  mcp-klever-vm

  Get summary statistics of the Klever VM knowledge base. Returns total entry count, counts broken down by context type (code_example, best_practice, security_tip, etc.), and a sample entry title for each type. Useful for understanding what knowledge is available before querying.

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• lookup_headers

  botoi-mcp

  Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.

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• describe_table_tool

  Wherobots

  Describe a specific table. ⚠️ WORKFLOW: ALWAYS call this before writing queries that reference a table. Understanding the schema is essential for writing correct SQL queries. 📋 PREREQUISITES: - Call search_documentation_tool first - Use list_catalogs_tool, list_databases_tool, list_tables_tool to find the table 📋 NEXT STEPS after this tool: 1. Use generate_spatial_query_tool to create SQL using the schema 2. Use execute_query_tool to test the query This tool retrieves the schema of a specified table, including column names and types. It is used to understand the structure of a table before querying or analysis. Parameters ---------- catalog : str The name of the catalog. database : str The name of the database. table : str The name of the table. ctx : Context FastMCP context (injected automatically) Returns ------- TableDescriptionOutput A structured object containing the table schema information. - 'schema': The schema of the table, which may include column names, types, and other metadata. Example Usage for LLM: - When user asks for the schema of a specific table. - Example User Queries and corresponding Tool Calls: - User: "What is the schema of the 'users' table in the 'default' database of the 'wherobots' catalog?" - Tool Call: describe_table('wherobots', 'default', 'users') - User: "Describe the buildings table structure" - Tool Call: describe_table('wherobots_open_data', 'overture', 'buildings')

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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 `project_id` field.

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• get_template_schemas

  RationalBloks

  Get pre-built template schemas for common use cases. ⭐ USE THIS FIRST when creating a new project! Templates show the CORRECT schema format with: proper FLAT structure (no 'fields' nesting), every field has a 'type' property, foreign key relationships configured correctly, best practices for field naming and types. Available templates: E-commerce (products, orders, customers), Team collaboration (projects, tasks, users), General purpose templates. You can use these templates directly with create_project or modify them for your needs. TIP: Study these templates to understand the correct schema format before creating custom schemas.

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• investigate_question

  VaultCrux Memory Core

  Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.

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• ping

  nara-tour

  Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.

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• list_databases_tool

  Wherobots

  List all databases in a given catalog. ⚠️ WORKFLOW: Call this after list_catalogs_tool to explore a specific catalog. 📋 PREREQUISITES: - Call search_documentation_tool first to understand what you're looking for - Call list_catalogs_tool to discover available catalogs 📋 NEXT STEPS after this tool: 1. Use list_tables_tool to find tables in a database 2. Use describe_table_tool to get table schemas before writing queries This tool retrieves all databases within a specified catalog. Parameters ---------- catalog : str The name of the catalog. ctx : Context FastMCP context (injected automatically) Returns ------- DatabaseListOutput A structured object containing database information. - 'catalog': The catalog name. - 'databases': List of database names. - 'count': Number of databases found. Example Usage for LLM: - When user asks for a specific catalog's databases. - Example User Queries and corresponding Tool Calls: - User: "List all databases in the 'wherobots' catalog." - Tool Call: list_databases('wherobots') - User: "What databases are in the foursquare catalog?" - Tool Call: list_databases('foursquare')

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• virtualsms_order_history

  sms

  List past orders with optional filters for status, service, country, and a lookback window in days. Returns up to 50 orders (server cap) ordered most-recent-first.

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• run_query

  VirtualFlyBrain

  Run a query on VirtualFlyBrain using a VFB ID and query type. Supports batch requests — pass an array of IDs to run the same query_type on all of them, or use the queries array for mixed ID/query_type combinations. When multiple queries are provided, results are returned as a JSON object keyed by "ID::query_type". IMPORTANT: Do NOT pass tool names (like "get_term_info" or "search_terms") as query_type — those are separate tools. Valid query_types are returned by get_term_info in the Queries array for each entity. Common query_types include: PaintedDomains, AllAlignedImages, AlignedDatasets, AllDatasets (for templates); SimilarMorphologyTo, NeuronInputsTo, NeuronNeuronConnectivityQuery (for neurons); ListAllAvailableImages, SubclassesOf, PartsOf, NeuronsPartHere, NeuronsSynaptic, ExpressionOverlapsHere (for classes). Available query_types vary by entity type — ALWAYS call get_term_info FIRST to see which queries are available for a given ID, as attempting invalid query types will result in an error message directing you to use get_term_info.

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• cdc_get_dataset_schema

  cdc-health-mcp-server

  Fetch the full column schema for a CDC dataset — names, data types, descriptions, row count, and last-updated timestamp. Essential before writing SoQL queries against unfamiliar datasets.

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