"NFT documentation and guides" matching MCP servers:

Provides AI assistants with access to Vega-Lite documentation, visualization examples, and specification validation tools. Enables searching docs, retrieving examples by category, validating JSON specs, and accessing schema information for creating data visualizations.

Enables AI assistants and other MCP clients to audit and manage Hex workspaces through the Hex API, covering projects, users, data connections, runs, cells, groups, collections, guides, and agent threads.

Enables AI agents and MCP clients to search the Scrape.ly Store for Actors, read their README and input schema, run them, follow runs, and read results from datasets, key-value stores and logs. It also supports managing saved tasks and searching the Scrape.ly and Crawlee documentation.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Exposes a synthetic issue tracker and pipeline warehouse as callable tools so an agent can answer operational questions about tickets, pipeline health, runs, incidents, and governed metrics with every claim cited to the exact tool call it came from. All writes are proposal-only, requiring human approval through a gated apply path that logs each step for audit.

Exposes local DuckDB pizza sales data as MCP tools for querying store-level and total sales metrics via natural language, enabling local LLMs to perform real-time analytical queries.

Transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement. Guides users through clarifying questions to gather comprehensive requirements for automated Business Intelligence dashboard generation.

Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.

Enables AI assistants to audit, profile, and govern dbt projects through natural language, including coverage scoring, schema drift detection, test suggestions, and non-destructive YAML documentation updates.

Enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language. It consolidates coverage analysis, data profiling, and safe YAML updates into a single MCP interface.

Enables AI assistants to audit dbt project coverage and health, profile warehouse data, detect schema drift, suggest tests, and generate or safely update model documentation through natural language.

Generates complete PyAirbyte data pipeline code and setup instructions for moving data between 600+ Airbyte source and destination connectors or to Pandas DataFrames, using AI-powered context-aware guidance based on connector documentation.

Provides stock market data and computes technical indicators like EMA, MACD, and RSI across multiple timeframes using the LongPort API and TA-Lib. It enables users to perform detailed financial analysis and multi-timeframe market reviews through standard MCP tools.

A conversational copilot that guides users through the Knowledge Discovery in Databases (KDD) process to perform automated data profiling, analysis, and modeling via natural language. It enables the creation of interactive dashboards and manages the end-to-end analytical workflow within a secure sandbox environment.

Enables AI coding assistants to assess dbt project health and test/documentation coverage, profile warehouse data, detect schema drift, suggest tests, and safely update schema.yml documentation through natural language.

Enables schema-aware exploration of JSON data by uploading samples, flattening nested structures, and using heuristic search with token overlap and fuzzy matching to find field paths for target names, accelerating ETL and API onboarding workflows.

It enables AI assistants to audit dbt project health, profile data, detect schema drift, suggest tests, and auto-generate documentation through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and safely generate or update schema.yml documentation through natural language.

Enables AI assistants to audit dbt project quality, profile warehouse data, detect schema drift, and auto-generate or update documentation and tests through natural language.

Enables AI assistants to audit dbt project health, profile warehouse data, detect schema drift, suggest tests, and auto-generate non-destructive schema documentation through natural language.