"General Inquiry about the Number 1" matching MCP servers:

Exposes a governed dbt MetricFlow semantic layer to AI agents through three tools — list metrics, list dimensions and query metrics — so questions about federal contract spend are answered from defined metrics rather than raw tables. Guardrails reject undefined metrics, raw columns, SQL in filters and bulk exports, and no tool can execute SQL.

Enables AI agents to discover and query data federated across MySQL/MariaDB, PostgreSQL, ClickHouse, S3 and Kafka with SQL, exposing tools to list databases, schemas, tables and connections, describe columns, search objects, inspect table statistics, run EXPLAIN, and execute arbitrary statements. It runs locally over stdio against a PostgreSQL-wire endpoint and returns structured results or SQLSTATE-coded errors.

Provides real-time and historical cryptocurrency market data from multiple exchanges (Binance, Kraken, Coinbase Pro) with Redis caching and rate limiting support.

Generates a random number between 1 and 10 using the StupidAPIs service. Part of the Pipeworx MCP gateway providing access to 673+ data sources.

MCP server that archives Decent DE1 espresso shots from Visualizer.coffee into SQLite and provides analysis tools for shots, beans, and profiles via MCP.

Enables AI agents to inspect schemas, walk Delta table history, run read-only DuckDB queries, and check data-quality and job-run status safely.

Enables AI agents to inspect, query, test, and safely fix dbt projects and BigQuery warehouses under policy-enforced controls, with read-only direct queries and dbt-only allowlisted writes.

An MCP server that gives models semantic context about a data warehouse, including table meaning, units, lineage, and health, to reduce guessing.

Enables environmental scientists to tidy PFAS lab files, screen results against two drinking-water guideline sets side by side, search public guidance with page-level citations, and check report text so every number traces back to its lab row or guideline page.

Enables looking up mobile phone numbers for a list of contacts by chaining your own Prospeo, Lusha, ContactOut, and FullEnrich keys until a provider returns a number. Returns one row per contact with the number in E.164 format, line type, country, a Do Not Call flag where reported, and the provider credits spent.

MCP server for Durable energy trading analytics that connects Claude Desktop to Snowflake data, enabling natural-language queries about spreads, constraints, generators, and prices.

Connect your ads, shop, analytics, social, CRM and finance platforms once, then let Claude, ChatGPT, Cursor or any MCP client read, join and explain your numbers. Public statistics from the World Bank, IMF, Eurostat, OECD, WHO and SEC filings come as context, searchable and chartable from the same tools. Read-only by design, every number carries its source.

Bridges Claude (or any MCP client) to manufacturing data via the i3X standard, enabling natural language queries about equipment status, hierarchy, and historical trends.

MCP server for Formula 1 data via the FastF1 library. Ask Claude (or any MCP-compatible client) about race results, lap times, telemetry, standings, pit stops, and qualifying — with historical data back to 1950 via the Ergast API.

Enables natural language queries about grades, GPA, attendance, and schedules by connecting Claude to StudentVue school dashboards. Includes analytical tools for grade simulation, what-if scenarios, and academic performance tracking based on live school data.

The JSON to Excel MCP provides a standardized interface for converting (1)JSON data (2)URL pointing to JSON files into CSV format

Enables you to interact with your Fivetran environment through natural language, supporting read-only queries about connections and syncs, and write operations like updating sync frequency when enabled.

A Model Context Protocol server that allows interaction with the RubyGems.org API to fetch metadata about Ruby packages, search gems, and explore dependencies and ownership information.

Provides comprehensive Formula 1 data access including race schedules, session results, lap times, telemetry data, driver/constructor standings, and circuit information. Enables users to retrieve and analyze F1 racing data through natural language queries using the FastF1 Python package.

Provides advanced Formula 1 analytics including real-time telemetry processing, tire degradation modeling, weather impact analysis, and Monte Carlo race strategy simulation for comprehensive F1 data analysis.