obot-platform/obot

Obot is an open-source platform for organizations to manage, secure, and govern their AI ecosystems. It provides shared infrastructure for connecting AI clients to models and tools, distributing approved MCP servers and skills, managing agent access and credentials, running hosted AI workloads, and recording activity across hosted services and user devices.
Obot does not require an organization to standardize on a single AI client, model provider, or tool ecosystem. Desktop agents and tools such as Claude Code, Codex, Cursor, VS Code, and other IDEs and CLIs can use the parts of the platform that apply to them.
## Architecture
The Obot Platform connects AI activity on user devices with services managed by or proxied through Obot Server.
On user devices, desktop agents and tools connect to Obot gateways, while Obot Sentry scans, audits, and enforces policy on AI activity taking place on the device. The Obot CLI lets users and AI clients discover, install, and manage approved MCP servers and skills.
Obot Server provides:
MCP and LLM gateways for controlled access to MCP servers and model providers.
Isolated execution for hosted MCP servers and Claude Environments sessions.
Platform services for identity and access control, including permissions and secrets.
Correlated audit logs of AI activity across the platform.
MCP and Skills registries built on curated Git-backed catalogs.
Obot integrates with remote MCP servers, LLM providers, S3-compatible object storage, Git providers, and auth providers.
## Core Capabilities
### MCP Gateway
The MCP Gateway is a single governed entry point to every MCP server a user is allowed to reach.
Expose MCP servers through virtual MCP servers (vMCPs), which combine one or more catalog servers behind a single endpoint, whether those servers are hosted by Obot or run outside it.
Reach remote MCP servers on private networks through MCP tunnels, which connect outbound to Obot so no inbound port has to be opened.
Pin each vMCP component to a snapshot of its catalog entry, so catalog changes take effect only through an explicit upgrade.
Control server and tool access by user or identity-provider group through vMCP profiles.
Enable tool search on large vMCPs so clients search for and call tools without loading every tool definition into the model's context.
Chat with and call tools on any vMCP you can access using the built-in MCP tester.
Manage MCP OAuth, user and shared credentials, and Kubernetes secret bindings.
Inspect, reject, or modify MCP requests and responses with MCP, webhook, or built-in credential filters.
### LLM Gateway
The LLM Gateway presents provider-compatible endpoints that AI clients use to reach approved models.
Connect external AI clients to OpenAI, Anthropic, Amazon Bedrock, Azure, and Generic Responses Compatible providers.
Keep provider credentials in Obot instead of distributing them to individual users or clients.
Authenticate clients with scoped Obot API keys.
Restrict the models visible and callable by each user through Model Access Policies.
Record requests and responses, client and session metadata, token usage, and estimated model cost.
### Hosted MCP Servers