"sql server" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
Data Oil is a multi-model database built for object storage. It uses a log-structured storage engine, snapshot isolation with optimistic commit, and a change feed from the write-ahead log. Its SQL dialect supports joins, window functions, CTEs, set operations, graph traversal and pattern matching. It has its own HNSW vector index and BM25 full-text index, and a write is searchable by keyword and vector as soon as it commits. Access is over HTTP, the PostgreSQL wire protocol (extended protocol). We have a founder's program available for projects which may be of interest https://dataoil.tech/founders.html if your interested lets chat ;)
Every spreadsheet is a table: upload Excel, CSV, Parquet or JSON files and query them in SQL (Apache DataFusion), with joins across formats, schema and column statistics. Hosted tableski server; connect with your tableski.io access token. Open source: github.com/yarenty/tableski
Read-only analytics on x402 agent payments and ERC-8004 agent identity, with SQL.
Hosted SQL Server MCP server for Claude, ChatGPT and Cursor, with each action switched per account.
Query Postgres, MySQL, SQL Server, Oracle, BigQuery, ClickHouse and Redshift from your AI client.
Backend brasileiro (Postgres, login, storage): a IA cria tabelas, liga RLS e roda SQL no projeto.
Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.
PDF, image, video, OCR, screenshot, SQL, QR and text tools for agents. No API key, no signup.
Read and edit DB Planner database schemas (DBML/SQL), Mermaid diagrams and board layouts from any MCP client. 40 tools with annotations and output schemas. OAuth sign-in, with read and write as separate scopes enforced server-side.
DBRE-grade SQL analysis inside any MCP client. No connection. No install. Paste a query.
Search ILOSTAT labour indicators, query and compare series, build country profiles, run SQL.
SQL validation, formatting, parsing, metadata extraction, linting, and security analysis.
Access control for text-to-SQL agents. Before the model sees the schema, schemagate keeps only the tables and columns the caller may read, picks the few a question needs, and refuses hidden ones at query time. This public endpoint serves a sample schema (no real data). Self-hosted it works with Postgres, Oracle, MySQL, SQL Server and SQLite.
Push CSV, TSV, JSON, JSONL or Parquet from your agent and get a link a human can explore: filters, column charts, SQL, pinned findings and what changed since the last push. Viewing is free, no signup; anonymous datasets live 7 days. Tools: push, pin_finding, get_dataset, list_datasets, delete_dataset, get_limits. Docs: https://rows.page/docs/mcp
Query a TikTok data warehouse (creators, videos, sounds, daily history) with read-only SQL.
Every figure re-checked against SQL-computed facts; unsupported questions refused with the reason.
Deterministic safety, correctness & cost gate that vets Postgres SQL before your AI agent runs it.
Executes SQL in a real ephemeral database: rows, typed errors with suggestions, plans, diffs.
AI access to Quadratic spreadsheets: open files, run Python/SQL, query connected databases.
Your Supabase account in natural language: run SQL, apply migrations, manage tables, storage, edge f
