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

Enables security researchers to evaluate AI system defenses against prompt injection attacks through a comprehensive set of test vectors and analysis tools.

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.

Enables users to scan untrusted text, files, and directory trees for prompt-injection patterns and receive severity-ranked, explainable verdicts before content reaches an agent. It runs locally and returns clean, review, or blocked verdicts for safer agent input.

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 MCP clients such as GitHub Copilot, Codex, Claude... to explore a SQL Server 2017+ database read-only: databases, schemas, tables, views, procedures, functions, indexes and dependency graphs, plus filtered, grouped, sampled and paginated queries capped by row limits.

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

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

Enables read-only SQL Server queries across multiple environments with secure keychain credential storage, catalog exploration, and built-in safety guards against destructive operations.

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

MCP server for SQL Server database inspection and querying, with connection pooling, security features, and a web manager UI.

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.

Read-only MCP server for SQL databases (SQLite/PostgreSQL) that enables listing tables, describing schemas, and executing SELECT queries with safety guardrails.

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.

MCP server for SQL Server database interactions, providing tools to list databases, get schema, and execute parameterized SELECT queries.

Gives AI coding tools reviewed access to PostgreSQL, MySQL, SQL Server, and SQLite databases, letting read-only queries run instantly while every data or schema change pauses for human approval in a review dialog. It also exposes schema introspection for agents and a way to open the connection manager.

An MCP server that gives LLM clients access to a SQL Server database and the local filesystem, including file operations and image handling.

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 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 querying of a SQLite database through a locally served, fine-tuned text-to-SQL model exposed as an MCP tool, offering fast and cost-free SQL generation and execution.

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

Automatically injects development framework context and workflows into Claude conversations, ensuring Claude follows your established patterns without manual context provision each time. Supports custom frameworks, keyword triggers, and Knowledge Graph integration.

Provides AI agents read-only analytical access to a SQLite database over stdio, with tools for listing tables, describing schemas, and running paginated SQL queries.

Enables running parameterized SQL queries against a PostgreSQL database via an MCP tool.

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

Provides SQL analysis, linting, and dialect conversion using SQLGlot, enabling validation, transpilation, and extraction of table/column references.

Enables LLM agents to read PostgreSQL data through a fixed catalog of parameterized, read-only queries, without allowing free-form SQL or access outside bounded inputs.