How to create an MCP connector (Company settings)

Step-by-step expectations for adding a new MCP connector in Company settings, syncing tools, and Endpoint AI review when enabled.

MCP connectors are added from Company settings → Integrations using New connector (wording in your tenant may match your theme). You step through a short wizard so Harriet can call an MCP server safely and attach it to skills.

Wizard outline

Basics — Display name and how the connector should appear to admins.
Connection — Pick how Harriet reaches the server:
- OpenAPI / Swagger — REST API via an OpenAPI spec URL and API base URL.
- Native MCP server — HTTPS JSON-RPC MCP endpoint (MCP server URL required).
- Sandboxed (uvx / npx) — Run a packaged MCP in an isolated environment (e.g. npx or uvx); you provide the sandbox command and arguments.
Authentication — Depends on type: no auth, basic auth, organization secrets, per-user OAuth (client ID when enabled), or patterns your deployment supports for sandboxed servers.
Access — Which groups or document scopes may use this connector, consistent with your permissions model.

Save the connector, then use Sync tools (or equivalent) so Harriet discovers tools and you can set tool permissions (including confirmation gates for risky operations).

Endpoint AI review

If your organization uses Endpoint AI, new MCP connectors may start in a draft state and require submit for review before they are deployable. Reviewers use the Endpoint AI console review queue to approve, reject, or request changes. Link from the connector configuration UI when present.

After configuration

Attach the connector to the appropriate skills (company settings or Endpoint AI skill authoring).
Restrict which channels, workflows, or users may invoke those skills.

See also How do we connect external tools using MCP?, MCP authorization and stored credentials, and Using Skilify to build skills locally, submit for review, and provision them when authors submit package skills that reference connectors.