"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.

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

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

Demonstrates deceptive tool naming and unsanitized shell execution by exposing tools that perform OS fingerprinting and run local system commands through MCP. Intended for security research on vulnerabilities in the MCP ecosystem.

Enables AI clients to safely query PostgreSQL databases using plain English, with read-only access and built-in SQL safety checks.

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.

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

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.

Enables AI assistants to safely explore and query MySQL, MariaDB, PostgreSQL, SQLite and StarRocks databases through read-only tools for schema listing, table description, schema search, row sampling, query execution, and plan explanation. Enforces least-privilege accounts, engine-level read-only sessions with timeouts, parsed SQL guardrails, and column masking so runaway or unsafe queries are refused.

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 an LLM agent to write and execute checked read-only SQL against databases containing personal data while receiving tokens instead of declared personal values, so it can still compare, group, count, and join without seeing the underlying data.

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.

Read-only MCP server for SQL databases (SQL Server, Postgres, SQLite) with multi-server support and three-layer safety using AST validation and linting.

Enables static, database-free SQL health checks that return rule-based findings and verdicts, propose executable fixes, and verify rewrites are equivalent while comparing execution plans and suggesting indexes. Supports batch/file/git-diff review for CI gating, all at zero-dependency Tier0.

Enables agents to scan untrusted text for jailbreak markers, prompt-override exploits, and indirect injection payloads, then cleanse it by replacing hostile command sequences with safe placeholders before the text reaches a prompt. Exposes tools for sanitizing input and itemizing detected threat patterns.

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 AI assistants to inspect PostgreSQL schemas and table metadata, preview SELECT queries with capped rows, and receive write or DDL statements for manual review without execution.

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 VS Code Copilot Chat and custom agents to interact directly with Microsoft SQL Server for queries, stored procedures, transactions, SQL Agent job management, schema discovery, and administrative tasks without PowerShell or sqlcmd.

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.

Dynamic MCP service for MySQL and PostgreSQL, allowing runtime database connections and SQL queries via tools.

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.

Enables natural language database interaction with SQLite through JMD documents, allowing CRUD operations and schema management via simple text format.

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