Database MCP servers
Read from Postgres, MySQL, or MongoDB without exposing raw connection strings. Agents query through a governed proxy with row-level access controls.
Model Context Protocol
Connect any data source via MCP
Model Context Protocol (MCP) is the open standard for connecting AI agents to external tools and data. AgentWorks treats every MCP connection as a governed connector — scoped, logged, and owned.
What is Model Context Protocol?
MCP is an open protocol created by Anthropic that defines a standard way for AI models to connect to external data sources and tools. Instead of building custom integrations for every service, you expose a compliant MCP server once — and any agent that understands the spec can use it immediately.
AgentWorks extends MCP with enterprise governance: every connection is proxied, logged, and scoped to individual agents. Your data doesn't flow directly from source to model.
Common MCP server types
File & document servers
Give agents access to specific folders or SharePoint libraries. Files are scoped per agent — no agent can read more than you explicitly allow.
Internal API servers
Expose internal REST or GraphQL APIs as MCP endpoints. Define which operations each agent may invoke and log every call.
Custom MCP servers
Build your own MCP server for any proprietary data source using the open spec. AgentWorks connects to any compliant endpoint out of the box.
Governance layer
MCP with enterprise controls
- Least-privilege access
- Each agent is granted only the MCP capabilities it needs. Nothing more.
- Full audit trail
- Every MCP tool call — inputs, outputs, timing — is recorded in the immutable log.
- Data boundary control
- Define which data may leave your perimeter. PII detection runs before data is sent to any model.
- Per-agent ownership
- Each MCP connection is owned by a specific agent and tracked separately for compliance reporting.