Problem solved

Organizations struggle to provide AI agents with secure, controlled access to internal tools and data. Lobu solves this by offering a centralized platform where companies can connect tools once, define access policies, and enforce approvals, ensuring agents only use permitted resources across different AI platforms.

Use cases

• Managing shared company context for AI agents
• Enforcing access controls and approvals for agent actions
• Connecting various AI interfaces (ChatGPT, Claude, etc.) to internal tools
• Running isolated agent executions for safety
• Standardizing tool access via MCP for custom agents
• Auditing agent actions across the organization

Audience

• Developers
• ML Engineers
• Enterprise
• Startups

Pros

• Open-source with self-hosting option for data control
• Permission-aware context sharing respects existing tool permissions
• Integrates with multiple AI platforms (ChatGPT, Claude, etc.)
• Supports MCP for interoperability
• Provides approvals and isolated execution for safety

Cons

• Requires self-hosting and maintenance (infrastructure overhead)
• Limited maturity (likely early stage, no enterprise track record)
• Documentation may be sparse (common in early open-source projects)
• Needs integration effort to connect company tools
• Potential complexity in managing scoped identities and permissions