"Techniques for Detecting XSS and SQL Injection Vulnerabilities" matching MCP servers:

An MCP server for identifying SQL injection vulnerabilities in web applications using various techniques like error-based, time-based, and union-based scanning. It supports bulk URL processing, WAF bypass strategies, and authenticated testing across multiple database systems.

Blocks indirect prompt injection by tracking data provenance, not text patterns. Enables safe agent interaction with untrusted content.

Scans MCP servers for prompt-injection, tool-poisoning, and SSRF vulnerabilities using 30+ canonical rules across 5 severity tiers, with optional signed safety reports for procurement.

Automatically scans SQLite databases and generates typed CRUD tools for each table, allowing natural language database interaction without exposing raw SQL.

A governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.

An MCP server that connects LLMs to SQL databases for development assistance, enabling query execution, schema exploration, and data manipulation while providing safety controls against destructive operations.

An AI-powered SQLite assistant that converts natural language to SQL queries with full schema awareness, enabling users to interact with databases using conversational language.

WAF for AI agents — block prompt injection before it reaches the LLM.

An extensible read-only MCP server for SQL databases, enabling schema exploration and safe SELECT queries via tools like list_schemas, list_tables, describe_table, and execute_query.

Enables AI agents to explore MySQL database schemas as structured models, inspect tables, columns, keys, revisions, and generate migration scripts through a read-only interface that never exposes row data or write access.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

MCP server that enables natural-language SQL queries across multiple databases (ClickHouse, Teradata, PostgreSQL, MySQL, SQL Server, DB2, Oracle, MongoDB) with dialect-correct SQL generation, PII masking, and security-by-construction controls.

Enables querying multiple SQL Server, Azure SQL, or Synapse databases through a single MCP interface, with support for read-only targets and various authentication methods.

Enables natural language and SQL querying across SQLite, MySQL, PostgreSQL, and MongoDB databases with support for bulk operations and schema inspection. It features a safety mechanism requiring explicit user confirmation for destructive actions like data modification and deletion.

Enables LLM agents to explore and query a Postgres database through secure, read-only tools.

Enables AI assistants to interact with SQL Server databases through tools for connectivity, schema exploration, SQL queries, and OEE metrics analysis.

Enables querying SQL Server databases using natural language through Claude.

Enables secure interaction with SQL Server databases through natural language queries in Cursor IDE, with individual user credentials for complete traceability and auditing of all database operations.

MCP server that integrates sql-sop SQL linter into LLM clients, enabling linting SQL queries and listing lint rules via chat tools.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.