Why connectors and MCP matter
The Model Context Protocol (MCP) is an open standard that lets AI assistants — like Claude, ChatGPT, Cursor, and others — securely talk to external systems through a common interface. A connector is simply an MCP server that exposes a specific product or service (in our case, Coconut) as a set of tools the AI can call on your behalf. Instead of copy‑pasting between tools or building bespoke integrations, connectors give your AI assistant real, live access to the systems where your work actually lives, while preserving the permissions of the signed‑in user. If you can’t see something in the source system, the connector can’t reach it either. Key benefits:- Live context — the assistant reads current state (tasks, jobs, knowledge) instead of stale snapshots.
- Actionable — beyond reading, it can create and update records on your behalf.
- Permission‑aware — every request runs as you, subject to your Coconut scopes and role.
- Portable — any MCP‑compatible client works the same way (Claude, Cursor, Windsurf, ChatGPT, custom agents, etc.).
The Coconut connector
The Coconut connector is an MCP server hosted at:What it can access
The Coconut MCP server exposes the following tools. Each tool is gated by a specific OAuth scope, so you can grant read‑only access or allow writes on a per‑capability basis.| Tool | Description | Required scope |
|---|---|---|
coconuts_list | List Coconut instances visible to the signed‑in user or active organization. | coconuts:read |
coconuts_health_list | Get health and latency for eligible Coconut instances. | health:read |
tasks_list | List tasks for one Coconut, optionally filtered. | tasks:read |
tasks_get | Get one task from a Coconut. | tasks:read |
tasks_create | Create a task on a Coconut you can modify. | tasks:write |
task_update | Update an existing task; only provided fields change. | tasks:write |
knowledge_search | Search knowledge documents on a Coconut. | knowledge:read |
knowledge_get | Get a knowledge document by filename or path. | knowledge:read |
knowledge_create | Create a knowledge document on a Coconut you can modify. | knowledge:write |
knowledge_update | Update an existing knowledge document. | knowledge:write |
context_get | Get one or more context documents (role, agents, team, memory). | context:read |
jobs_list | List jobs for one Coconut. | jobs:read |
jobs_get | Get one job definition from a Coconut. | jobs:read |
connectors_catalog_list | List available connectors in the Coconut control plane catalog. | connectors:read |
Add the Coconut connector to Claude
Claude supports remote MCP servers as custom connectors. The steps below are adapted from Anthropic’s official guide.Custom connectors are available on Claude, Cowork, and Claude Desktop for users on Free, Pro, Max, Team, and Enterprise plans. Free users are limited to one custom connector. On Team and Enterprise plans, an Owner or Primary Owner must enable the connector for the organization first.
Open connector settings
In Claude, navigate to Customize → Connectors. Click the + button next to Connectors.
Enter the Coconut MCP details
Use the following values:
- Name:
Coconut - URL:
https://app.coconut.dev/mcp
Connect and authenticate
Click Add, then follow the OAuth prompts to sign in to Coconut and grant the scopes you want the assistant to use (for example,
tasks:read, knowledge:write).Other MCP clients
Because the Coconut connector is a standard remote MCP server, any MCP‑capable client works the same way. Point your client at:Security and permissions
- All traffic to
https://app.coconut.dev/mcpis encrypted in transit. - The connector never escalates privileges — tool calls execute as the authenticated user, subject to your Coconut role and scopes.
- You can disconnect the connector at any time from your AI client’s connector settings, which revokes its ability to call Coconut tools.
- On Team and Enterprise Claude plans, Owners can restrict write‑scoped tools (e.g. allow
tasks:readwhile blockingtasks:write) org‑wide.