"Automating guard duty alert validation and reporting process" matching MCP servers:

A cooperative guardrail for AI agents that blocks destructive shell commands, SQL statements, or cloud operations until a human approves them out-of-band, with a tamper-evident local ledger.

Enables AI agents to safely query and explore SQLite databases through read-only, guard-protected tools that block writes, sensitive table access, and runaway queries.

Lets AI agents estimate the cost and result size of BigQuery and Snowflake queries before they run, then execute them only within per-call byte, row, and dollar bounds. Estimates are labeled with an accuracy tier so agents never over-trust an approximate figure.

An MCP server that enables AI agents to securely interact with PostgreSQL databases with least-privilege scopes, PII masking, and human approval for writes.

Enables read-only PostgreSQL interaction through safe query execution, query planning, table and column inspection, and privilege checks, with multi-layer defenses against write operations and transaction-control exploits.

Enables estimating a BigQuery query's cost before running it, using a free dry run to report bytes processed and the estimated on-demand USD charge. It also flags common sources of wasted spend, such as SELECT * and missing partition filters on partitioned tables.

Audits PostgreSQL/Supabase schemas for security issues like missing RLS, permissive policies, and sensitive data exposure during AI conversations.

Enables AI agents to run BigQuery queries safely under a configurable policy, with parsing, dry-run byte limits, row caps, and audit logging for every request.

Enables safe, read-only interaction with Redis databases via cursor-based tools for retrieving keys, hashes, lists, sets, and sorted sets, backed by ACL DRYRUN-verified privilege checks.

Exposes tools that let AI coding agents browse a repo's schema snapshot of tables and columns and validate their SQL against it before running or writing it, so queries referencing invented or stale table and column names get caught and corrected up front. Provides list_tables, describe_table, search_columns, and check_sql over the same snapshot used by the CLI, hook, and CI check.

A security proxy for Neon's MCP server that allows AI agents to create and manage isolated test branches with a default-deny whitelist, provenance gating, and short-lived credentials, while air-gapping production data and master keys.

Enables AI agents to safely work with SQLite databases by enforcing read/write separation, dry-run writes with confirmation, automatic backups, and an audit trail.

A local policy wrapper for Supabase MCP that secures access tokens and enforces strict execution models, including project allowlists and write-access restrictions. It provides a safety layer to prevent AI agents from accidentally executing migrations or writing SQL against production environments.

Validates SQL queries via AST parsing, ensuring they are single read-only SELECTs on allowed tables with enforced LIMITs, and masks PII columns based on user roles. Provides a tamper-evident audit log and runs fully offline.

Enables AI agents to safely query PostgreSQL by intercepting and auditing every generated SQL statement before it reaches the database, blocking destructive commands like DROP/TRUNCATE, unbounded DELETE/UPDATE statements, stacked queries, and SQL injection probes. It exposes tools for validating query safety and enforcing a strict read-only (SELECT/EXPLAIN) policy.

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

Search the fastest-growing US horse boarding directory: 6,000 facilities and 3,800 trainers across 48 states, plus boarding price data by state.

A tool that integrates process mining capabilities with Claude AI, allowing users to analyze event log data from PostgreSQL databases through natural language interfaces in Claude Desktop or Cursor.

Enables AI agents to query and modify MySQL and MariaDB databases over MCP, with each connection independently permitting selects, inserts, updates, deletes, and DDL while defaulting to read-only and rejecting anything outside the allowed operations. Connections are configured in JSON, result sets are capped and truncated, and passwords stay server-side.

A read-only MCP server for the FinDB demo database, exposing customer, account, card, and transaction reporting tools over stateless Streamable HTTP.