"A server for finding botanic data" matching MCP servers:

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

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.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

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

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

An MCP server for data reconciliation between MySQL and Snowflake, enabling LLM agents to validate data integrity during migrations and ETL processes.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

Enables AI clients to investigate data engineering workflows by exposing tools for job status, logs, schema lookup, read-only SQL, and searching documentation/incidents, along with resources and prompts for ETL failure analysis.

Provides seamless access to iRacing's racing simulation data, enabling AI assistants to retrieve driver profiles, career statistics, and team information. It features automatic authentication and tools for real-time driver lookups and season performance analysis.

Enables AI assistants to query and interact with Treasure Data through a secure interface, supporting SQL queries, database exploration, CDP segment management, and workflow monitoring across multiple regions.

Provides read-only, guarded access to business databases via MCP. Enables natural language querying with built-in security barriers like table allowlists, PII masking, and audit logging.

Enables MCP clients such as Claude, ChatGPT and Cursor to answer business questions about sales, customers, orders and spreadsheets in natural language by reading live Postgres/SQLite databases and Google Sheets without exporting files or gaining write access. Guardrails include AST-based read-only SQL validation, read-only database roles, row/byte caps with pagination, PII masking, bearer-token auth for remote HTTP use, and a full JSONL audit log of every tool call.

Provides secure integration between MCP clients and IBM Data Intelligence services, enabling AI assistants to interact with IBM's data intelligence capabilities for data management and analytics operations.

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.

An MCP server that connects AI agents to cloud-native geospatial data via STAC metadata and DuckDB with H3 spatial indexing, enabling zero-configuration SQL queries on terabyte-scale datasets over S3.

An MCP server that gives AI assistants the ability to connect to, query, profile, and monitor data sources — turning any LLM into an interactive data engineering copilot.

A read-only MCP server for securely querying MongoDB and Firestore to access customer and order data.

Enables LLMs to query a fintech database through predefined tools, returning structured customer credit, limit, and risk data while enforcing read-only access.

Exposes a governed lending portfolio (loans, customers, risk-tier history) to any MCP-compatible AI client via read-only tools, schema resources, and analysis prompts, wrapping an existing API gateway instead of connecting directly to the database.

Enables LLM clients to access governed data platform metrics and schema descriptions through exactly three read-only, authenticated, validated, bounded, and audited tools.