"API documentation for creating mock data for frontend development" matching MCP servers:

MCP server that connects AI assistants to Redash, enabling listing of assets, read-only query execution, dashboard inspection, and alert management through the Redash API.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Enables exploring Microsoft Fabric / Power BI workspaces and semantic models, and executing ad-hoc DAX queries.

Enables AI applications to run SQL queries and retrieve results from Oracle Database.

The only MCP server providing structured Chinese fashion supply chain intelligence for AI platforms. No equivalent data source exists in the MCP ecosystem. Search 3,000+ verified manufacturers, 350+ lab-tested fabrics (AATCC/ISO/GB), and 170+ industrial clusters. Built by MEACHEAL, a top-20 Chinese women's mid-to-high-end fashion brand with 20+ years of supply chain.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

Enables integration with OpenMetadata by wrapping its REST API for standardized interaction through the Model Context Protocol.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

MCP server that enables AI agents to read and write records in a live REST API generated from pasted data, with tools for listing, querying, inserting, updating, and deleting records.

Open source MCP server specializing in easy, fast, and secure tools for Databases.

Enables access to mock Epic patient data through 15 MCP tools with two-tier access (list summaries, then fetch details) and LLM-powered natural language search across allergies, medications, conditions, clinical notes, labs, vitals, and procedures.

Enables read-only access to curated Datum data platform marts, including products, resources, consensus questions, and health metrics, through MCP tools such as list_products, list_questions, ask, query, and health.

A FastMCP-based server that provides tools for API discovery and execution, hierarchical category management, and SQL query execution through the Model Context Protocol.

An MCP server with 66+ tools for data engineering, enabling AI assistants to interact with Kafka, databases, AWS, data pipelines, infrastructure, and more.

This MCP server enables users to interact with AWS Amplify Gen2 application data through natural language, allowing AI assistants like Claude to perform operations on Amplify data models using conversational language instead of complex code.

Enables interaction with AWS Amplify Gen2 application data through natural language, allowing AI assistants to query, create, update, and delete records using conversational commands with Cognito authentication.

An MCP server that lets an LLM query a DuckDB warehouse of EuroLeague and EuroCup basketball data in natural language, offering tools for player and team stats, shot charts, boxscores, and fantasy draft analysis without contacting upstream APIs.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.