"Spring Security" matching MCP servers:

Deterministic encode, decode, hash and convert for agents, on the same pipeline engine as the String Utility Belt web app, CLI and editor extensions: a pipeline built and checked in the browser runs unchanged from its share link. Base64/hex/URL, JWT, hashes, JSON/YAML/CSV/XML, dates and regex; tools to search, describe and run utilities or whole pipelines, and to detect input formats. Runs locally

A read-only MCP server for querying SQL Server Analysis Services (multidimensional cubes via MDX and tabular models via DAX) using Windows Integrated Security.

Enables monitoring and managing Debezium/Kafka Connect CDC connectors, including status, configuration, lifecycle operations, and security controls, through natural language in MCP-compatible clients.

Enables interaction with Vertica databases through SQL queries, schema management, and bulk data operations. Supports connection pooling, SSL/TLS security, and configurable permissions for database operations.

Enables read-only access to FileMaker databases through the Data API, allowing users to retrieve records, analyze metadata, search across layouts, and infer relationships while maintaining data security.

Enables querying and managing SAP Cloud Platform Integration resources such as packages, integration flows, message processing logs, security material, and artifact lifecycle through the CPI OData v2 API.

Enables management of GitHub workflows, issue templates, and repository configuration for the Frontal MCP Server project through CI/CD pipelines and security automation.

Enables AI agents to securely interact with multiple databases (MySQL, PostgreSQL) via natural language queries, with cross-database querying and enterprise-grade security.

Enables access to BitSight security rating data through company search and rating retrieval functionality. Automatically manages BitSight subscriptions for one-time rating requests and provides structured security assessments for companies.

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

A governed MCP server enabling LLM agents to query BigQuery, inspect GCS, trigger Airflow DAGs, and run data-quality checks with built-in security guardrails like allow-lists, cost ceilings, and audit trails.

Provides read-only Microsoft SQL Server database access to AI agents with row-level security, enabling SELECT queries, table metadata, and schema introspection through MCP.

Enables management of Google Cloud Dataproc clusters and jobs through 22 production-ready tools, featuring intelligent parameter injection, semantic search capabilities, and enterprise-grade security for seamless big data operations.

Enables secure interaction with multiple SQL database engines (MySQL, PostgreSQL, SQLite, SQL Server) through a standardized interface. Supports schema inspection, safe query execution, and controlled write operations with built-in security restrictions.

Enables dynamic format selection (JSON, Parquet, Arrow IPC) for MCP tool outputs, with a Java Spring Boot server and Python client for agentic data systems.

Enables AI assistants to interact with security data pipelines and map data to the Open Cybersecurity Schema Framework (OCSF) through Tenzir. Provides seamless integration for processing and analyzing cybersecurity data using natural language.

An MCP server that enables AI assistants to interact with Tenzir, a data pipeline engine for security operations, including executing pipeline queries, managing OCSF schemas, and generating parsers.

Enables AI agents and assistants to work with a Databricks workspace — SQL, clusters and warehouses, notebooks, Jobs, Lakeflow pipelines, Unity Catalog, Volumes, dashboards, Genie, model serving, Vector Search, Lakebase and Apps — under a safety-first model with read/write/destructive/security classification, confirmation steps for dangerous changes, production resource protection, and a fully read-only mode. Every call is checked against the official Databricks SDK, returns typed schemas and redacted secrets, and unsupported features report an explicit error rather than faking results.

Full-featured MCP server for Apache Superset — 135+ tools for dashboards, charts, datasets, SQL Lab, security (users, roles, RLS, groups), audit, and more. Built-in safety validations.

Enables AI assistants to securely connect to Snowflake data warehouses and execute SQL queries through natural language interactions. Supports multiple authentication methods and provides formatted query results with built-in security controls.