"Development tools for API integration, security testing, and code quality" matching MCP servers:

CP server for RAD Security, providing AI-powered security insights for Kubernetes and cloud environments. This server provides tools for querying the Rad Security API and retrieving security findings, reports, runtime data and many more.

MCP server that lets AI coding agents (Claude Code, Cursor, Cline) audit Supabase projects for security misconfigurations AND apply the fixes — without leaving the agent. Tools: audit_project, list_findings, preview_fix (BEGIN/ROLLBACK safety), apply_fix (with confirmation), apply_all_fixes (transactional bulk). Closes the audit-fix loop entirely in the agent — other Supabase scanners only report.

MCP server for automated AWS security scanning — 19 modules, risk scoring, zero write operations.

Generates and deploys Cloudera Data Engineering (CDE) Airflow jobs from ODCS data contracts, validating live table data in CDW against schema and data-quality rules without WAP staging.

MCP server for Appwrite security audits that scans permissions and provides structured fix proposals, with active live leak confirmation via anonymous fetch.

A Model Context Protocol server that connects AI assistants like Claude to AWS security services, allowing them to autonomously query, inspect, and analyze AWS infrastructure for security issues and misconfigurations.

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

An MCP server for automated AWS security scanning. It detects over-privileged IAM roles and S3 Public Access Block misconfigurations, enabling least-privilege enforcement through tools like list_iam_roles, analyze_iam_policy, and analyze_s3_security.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Security Graph MCP Server

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

MCP Server for Google Cloud Healthcare API enables Agentic AI for a variety of FHIR-based digital health solutions, from smarter clinical workflows for Health Systems to Pre-Auth frameworks for Payers!

Linked API MCP server connects your LinkedIn account to AI assistants like Claude, Cursor, and VS Code. Ask them to search for leads, send messages, analyze profiles, and much more – they'll handle it through our cloud browser, safely and automatically.

The Hostinger MCP server enables seamless integration of Hostinger’s API with AI tools. This server exposes Hostinger API endpoints as callable tools, allowing AI models to fetch live data or perform real-time actions on hosting infrastructure.

An MCP server for HPE Juniper Security Director Cloud that exposes 368 tools to manage firewall policies, NAT policies, security resources, and more via the full OpenAPI surface. Enables LLMs to directly interact with and configure a live Security Director Cloud environment.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables execution of Snowflake stored procedures through the MCP server by providing a framework to define, manage, and call procedures from specific schemas or individual procedures.

Enables management and analysis of AWS security groups, S3 buckets, and VPC connections via MCP.

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.

A token-efficient MCP server for the Heroku Platform API that uses a search-and-execute pattern to minimize context window overhead. It enables secure app management through just-in-time endpoint discovery and built-in safety guardrails for API mutations.