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

Security analysis for Python codebases through the guard-core engine: SecurityConfig validation that catches keys pydantic silently drops, docs search over the vendored corpus, live detection probing, and verified setup guidance for Python, Typescript, Rust, PHP and Go adapters.

Check a backtest before trusting it: deflated Sharpe, CSCV overfitting, minimum track record length, breadth ceiling and paper-evidence checks. Deflated Sharpe and track record are tested in CI against the papers' worked examples, CSCV against CRAN pbo. Runs hosted with no signup, or fully on your machine in private local mode. Also reads SEC-reported company financials by ticker.

MCP server that gives AI agents paid tools to de-risk costly actions: dependency vetting, x402 endpoint verification, JSON repair, and URL reading. Fronts the Guard HTTP API at guard.fabtally.com.

Enables AI assistants to scan Terraform and Dockerfiles for security misconfigurations, returning structured Checkov findings that can be explained in plain language.

Enables AI agents to look up and assess credit risk for England & Wales companies, searching by name, retrieving R-Scores with financials, charges, CCJs and directors, fetching verified contacts, and batch-enriching up to 50 companies per call.

Enables large language models to automatically report customer-facing issues with Azure resources by parsing natural language requests and submitting impact reports through the Azure Management API.

Enforces deterministic policy decisions on AI agent tool calls, supporting allow, deny, correct, escalate, and human review actions with verifiable audit receipts.

MCP Guard Server - Budget control, approval workflows and audit logging for AI agents (Claude Code, Cursor, ChatGPT)

Enables deterministic policy enforcement for MCP and WebMCP tool calls, blocking boundary-crossing invocations and requiring exact human approval for consequential actions.

MCP server that gates premium features behind a combined x402 (USDC per call) and Stripe API key paywall, ensuring only paying users access deep functionality while free tier runs locally.

Scores prose from inline text or files on a 0–100 scale for formulaic AI writing patterns using rule-based heuristics, with no LLM judge or API calls. Returns band labels, specific violations with context, penalty breakdowns, and concrete advice for each hit, so agents can flag and revise sloppy generated text.

Enables agents to lint prose for formulaic AI writing patterns through the check_slop and check_slop_file tools, returning a 0–100 score, band label, specific violations with context, and concrete revision advice. Scoring is purely rule-based with no LLM judge or API calls, and custom rule configurations can be supplied.

Scans GitHub Actions workflow files for dangerous triggers, template injection, unpinned actions, excessive permissions, and secrets in shell commands before they are committed, exposing the checks as MCP tools for agents.

An MCP server that provides a guarded interface to the mem9 persistent memory backend, protecting AI agents against prompt injection, secret leakage, and memory poisoning.

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.

Enables coding agents to perform advisory runtime safety checks by inspecting proposed file paths and shell commands, tracking caller budgets, detecting repeated actions, and masking common credentials in output without executing commands or opening target files.

Enforces deterministic policies on AI agent tool calls, evaluating actions against compliance modules (SOC 2, HIPAA, GDPR, etc.) and returning ALLOW, BLOCK, or CONSTRAIN decisions with an audit trail.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

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.