What I like best about Willow is that it makes using AI with company tools feel much safer, clearer, and more organized, without making the experience complicated.
I like that everything goes through one governed gateway, so access, permissions, guardrails, security policies, and logs are handled in one place instead of being spread across different tools and setups. We can control exactly which tools and MCPs to add or remove, map IdP groups to the right MCPs and toolkits, and choose the authentication method for each MCP. That makes it much easier to manage who can access what and reduces the risk of giving AI agents too much access.
I also really like the automatic risk assessment for tools. It saves time and helps classify tools based on their risk. The separation between read tools and write tools is also very helpful from a security perspective, because it makes it easier to decide which actions are safe to allow and which need stricter control. The fact that Willow has many prebuilt MCPs maintained by Willow, plus official and community MCPs, while still letting us bring our own MCPs, makes it feel very customizable.
Another thing I like is the flexibility. We can install MCPs locally while still keeping the tools controlled and tracked through Willow, create plugins, assign skills to toolkits, and build toolkits that group multiple things together logically. In our org, for example, we create a toolkit (bundle of MCPs) for each team based on their needs, and then deploy it easily using an MCPB file through our MDM. This makes the onboarding process smooth and seamless for users. They open their MCP client, and the MCPs they need are already there, with the right access and security controls already applied.
Willow is also easy to debug and manage. The admin area and dashboard feel fast, modern, and easy to work with. The connection guides and integration configuration docs are clear and step-by-step, so setting up new integrations does not feel painful. It also gives better visibility into what is connected and how it is being used, which is important for both troubleshooting and security.
The Shadow MCP feature is also very helpful. It helps us discover unmanaged MCPs and tools running on endpoints, so we can see what is being used outside of the official setup. This gives us better visibility, helps us identify risky tools, and makes it easier to remove them or bring them under proper governance.
It also feels like Willow has a solution for many real-life cases. For example, if we want to use an n8n MCP that is hosted in a different private network and Willow cannot reach it directly, we can configure it as a local MCP. The MCP can run on a machine that has access, while the tools are still controlled, governed, secured, and tracked in Willow.
Overall, Willow gives me more confidence when using AI in real work environments, especially when the tools connect to sensitive business systems. It has a lot of advanced options and strong security controls, but the UI/UX still feels friendly and easy to use.
What I like most about Willow is that it doesn’t try to change how your team works. Instead, it sits in the middle and lets AI agents securely connect to the tools you’re already using. We use integrations with GitHub, Jira, Confluence and Figma, so it’s really convenient having everything managed from one place instead of configuring access for each tool separatly. It fit into our workflow pretty naturally and we were up and running without much effort.
The product also moves fast. New features show up pretty regularly, so it never feels like it’s standing still. Every now and then something gets released before the docs fully catch up, but it has never been a blocker for us. In those cases the support team was always quick to help.
One thing that really stood out for me is the support. The Slack channel has been great. Whenever we had a question or hit an edge case, someone got back to us really quickly with a useful answer. That made the onboarding process much smoother then I expected.
Overall, Willow made it much easier to put some governance around AI usage without slowing people down. Having one place to control what AI agents can access, together with integrations into the tools we already use every day, has been the biggest benefit. I haven’t had any major issues with it so far, which honestly isnt something I can say about every platform we use.
AR
Alex R.
Engineering Leader | Agentic AI in production | Fintech & Distributed Systems
Willow works well across integrations, performance, and usability. The connectors are reliable, the dashboard is clear, and the support team is fast, helpful, and easy to work with. The intelligence layer adds real value without making the workflow complicated.
Your enterprise just gained a new workforce. AI agents are already inside your systems, touching Jira, GitHub, databases, and Slack autonomously, on behalf of employees, right now. With no identity. No audit trail. No one watching.
On-prem got Active Directory. SaaS got Okta. The AI agent era has been missing its layer. Until now.
Most security platforms stop at visibility. Willow is built for what comes next: turning visibility into governed enablement, so every department can go full-blown AI without a security review backlog.
Willow is the Basecamp where every AI agent gets a real identity tied to your IdP, and governed access to exactly the tools and skills the task requires. Not just "can this agent connect to Jira." What it can actually do inside Jira. Action-level permissions. Least privilege enforced at runtime. Full audit on every interaction.
One entry point. Any agent. Claude, Cursor, ChatGPT, Gemini, Codex, n8n, custom. 100+ pre-built integrations. Skills registry with versioning. API-to-MCP conversion for legacy systems. Slack-native approvals. Endpoint sensors that surface shadow AI in real time, before it becomes an incident. SOC 2 Type II.
Visibility, control, and enablement. No tradeoff.
Your agents are already in the wild. Give them a Basecamp.