"SolidWorks control and automation methods" matching MCP servers:

An open-source MCP server that gives parents real-time oversight and guardrails over their children's AI agent interactions, with features like content filtering, spiral detection, and approval flows.

The control plane for AI prompts that scores, enforces policy, locks config, and audits every prompt decision.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

Enables AI agents to interact with Home Assistant through tiered, human-gated access: free reads and reversible comfort controls, while sensitive actions like locks, alarm, covers, and climate changes require per-operation human approval via Matrix.

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.

Secures MCP tools as an OAuth 2.1 resource server, validating short-lived delegated tokens, enforcing policy-as-code, and auditing AI agent actions.

A hardened MCP gateway that lets AI agents securely call infrastructure APIs like Kubernetes, Terraform, and Jenkins, with authentication, rate limiting, and OPA policy enforcement.

Provides search, detail lookup, and gap listing tools for a security control inventory, enabling natural language queries about control status and gaps.

Provides AI agents with programmatic access to Zscaler AI Guard, enabling autonomous management of detection policies, match rules, LLM applications, and LLM providers.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Enterprise AI governance layer for spend tracking, runtime guardrails, policy enforcement, and budget limits. Connects Claude, ChatGPT, and any MCP client to ThinkNEO's control plane for SOC2/GDPR/HIPAA compliance monitoring and real-time provider health.

Enables AI apps to securely connect to your Chirp home automation, letting you query sensors, control devices, manage automations, view alerts, and more through natural language.

Governs AI agent tool calls by checking them against Agentic Control Plane policies, returning allow/deny/ask decisions with audit logging and identity attribution for MCP clients like Claude and ChatGPT. Exposes acp_check and acp_status tools for policy enforcement and connection verification.

A local observation-only MCP server for macOS that provides secure, atomic evidence capture with strict target approval and manifest-based output.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

Validates URLs and checks their reputation to help identify AI hallucinations and verify web page authenticity.

A governed MCP server that enforces OAuth 2.1 scope checking and policy-driven access control for AI agents, providing a full audit trail on every tool call. It includes tools for Cisco Webex Contact Center knowledge search and SD-WAN network operations.

Stateless Streamable HTTP MCP endpoint with OAuth 2.1 authentication via Cloudflare Workers, supporting PKCE, DCR, and token introspection.

Enables generating secure passwords, exposing password policies, and providing reusable prompt templates for secure password creation through MCP primitives.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.