Search Results for "teams"

...By integrating with MCP-aware systems, Gate22 helps maintain security and compliance while enabling teams to scale agent-enabled workflows without losing observability into what actions are taken and why. It can be used to enforce fine-grained policies that restrict dangerous or unauthorized operations, track which agents are calling which tools, and record metadata for auditing and debugging.

...The project emphasizes repeatability and clarity, enabling teams to follow best practices for scalability, security, and operational reliability without hand-crafting deployment scripts for every new service. It supports integration with popular cloud providers and infrastructure tooling, streamlining workflows that span local development through staging and production environments.

...The project is aimed at solving common enterprise rollout problems such as reliably hosting servers for internal and external users, curating “approved” MCP servers for employees to find, and enforcing authentication, access control, and auditable activity. It also supports building richer agents and chatbots that can leverage MCP servers while keeping operations manageable for IT and platform teams. The platform is designed to work with a variety of workflows and clients, so MCP servers managed inside Obot can be used by automation/agent frameworks as well as popular chat clients that speak MCP.

Unla is a lightweight, highly available MCP gateway written in Go that turns existing MCP servers or ordinary HTTP APIs into MCP-compliant services through configuration, not code changes. Its goal is to let teams “wire up” tools they already run—internal REST endpoints, third-party APIs, or local MCP servers—and present a single, reliable MCP interface to clients like Claude Desktop, Cursor, and IDEs. The gateway focuses on operational concerns you’d expect in production: multi-instance availability, health checking, and declarative routing that maps upstreams to MCP tools and resources. ...

Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in...

...The repository and site describe it as “the one MCP to manage all your MCPs,” with diagrams and examples showing how to compose fleets behind a single endpoint. It ships Dockerized for quick deployment and emphasizes dynamic aggregation so teams can register or remove servers without restarting clients. The org maintains related repos and a GUI app for cloud and self-hosted setups, with a note that the cloud demo is outdated while the open-source v2 evolves. Overall, MetaMCP aims to simplify multi-server MCP operations for individuals and organizations.