Retrieve detailed information about a specific scheduled query by ID, including SQL code, schedule configuration, and metadata for security monitoring analysis.
Python
Apache 2.0
139,663 tools. Last updated 2026-05-26 12:58
"Information about SQL (Structured Query Language)" matching MCP tools:
- Save natural language and SQL query pairs to use as few-shot examples for generating SQL from questions.MIT
- Create and save SQL queries for later reuse in Apache Superset by providing query data including database ID, schema, SQL text, and display name.MIT
- Retrieve details of a saved SQL query from Apache Superset by its unique ID to access SQL text and database information.MIT
- Retrieve details about a saved blockchain data query from Dune Analytics, including SQL code, parameters, name, tags, and current state.MIT
- Query Goodday project management data using natural language to retrieve information about projects, tasks, and users without modifying any data.MIT
Matching MCP Servers
- AlicenseAqualityAmaintenanceA general-purpose MCP server that lets AI work with multiple databases within clear boundaries.Last updated134MIT
Structured-shofficial
Alicense-qualityCmaintenanceMCP server providing managed persistent memory for AI agents. Read and write structured state across sessions, tools, and restarts at 1000+ requests per second, with no infrastructure to self-host or operate.Last updated2Apache 2.0
Matching MCP Connectors
Autonomous A2A marketplace providing AI-ready, structured USPTO patent JSON datasets. Features IPC/CPC Sections G (Physics/Computing, e.g., G01 Sensors, G06 AI/ML) and H (Electricity, e.g., H01 Semiconductors, H04 5G). Enables instant M2M data delivery via automated on-chain payment verification. Networks: Base (USDC), Polygon (USDC), Oasis (ROSE).
A fully autonomous, Agent-to-Agent (A2A) patent data marketplace powered by the Model Context Protocol (MCP) and A2A standards. This server provides highly structured, AI-optimized JSON patent datasets curated for autonomous R&D agents, LLMs, and Quants. Currently exclusively hosting AI-ready patents from IPC/CPC Sections G (Physics & Computing) and H (Electricity).
- Process natural language queries about genomics data to generate structured AllianceMine queries for searching genes, diseases, expression, and molecular interactions across multiple organisms.MIT
- Query ServiceNow data using natural language questions to retrieve structured information from ITSM, ITOM, HRSD, and other modules.MIT
- Retrieve predefined tree-sitter query templates for code analysis. Specify the language and template type (e.g., functions, classes) to obtain structured query information for enhanced code context management.MIT
- Convert natural language questions about data into SQL queries using AI, enabling database interaction without SQL expertise.MIT
- Query information about IP addresses to retrieve metadata, using the Netdetective API for network investigation and analysis.MIT
- Query Wolfram Alpha for computational, mathematical, scientific, and factual information using natural language. Get answers about chemistry, physics, geography, history, art, astronomy, and more.
- Retrieve detailed column information for Teradata database tables, including data types and constraints, with SQL query metadata returned.MIT
- Generate schema-aware query suggestions with ready-to-run SQL to help explore unfamiliar databases and find useful queries.MIT
- Improve SQL query performance by analyzing execution issues and providing rewritten queries, explanations, and index recommendations.MIT
- Translate a natural-language question into an SQL statement using an LLM. Review the generated SQL before executing it with run_sql.MIT
- Retrieve all business glossary terms for a database connection, including plain-language definitions, SQL expressions, and related tables.MIT
- Retrieve saved natural-language to SQL example pairs for a database connection to guide SQL generation.MIT
- Answer natural-language questions by automatically generating and executing SQL, returning a Markdown report with summary, highlights, and data preview.MIT
- Define a business glossary term that maps plain-language phrases to SQL expressions. Teach the semantic layer common business terms for consistent query generation.MIT