MCP Server

claude — ~/projects/frontend

›look at my tickets in “To Do” and make a plan for how I should prioritize and finish them

janet-ai - list_tickets (MCP)(project_key: “SW”, status: “To Do”, assignees: [“me”])

You have 4 tickets in To Do. Here’s how I’d tackle them:

1. SW-84 SSO token refresh — blocking other auth work, fix first

2. SW-71 OAuth callback timeout — related to SSO, do right after

3. SW-63 Session cookie fix — standalone, quick win

4. SW-58 Safari redirect — lowest impact, last

Want me to spawn agents to start working through these?

›

Give AI agents like Claude Code, Cursor, and Codex full access to your Janet AI workspace. Create & resolve tickets, manage sprints, and more.

Setup

Run this command in your terminal:

claude mcp add janet-ai --transport http https://mcp.janet.ai/mcp

Then run /mcp in Claude Code and complete the OAuth flow to connect your Janet AI Organization.

Open Settings → Connectors → Add custom connector and enter the URL:

https://mcp.janet.ai/mcp

Complete the OAuth flow to connect your Janet AI organization.

Remote MCP servers in Claude Desktop are configured through Settings → Connectors, not the claude_desktop_config.json file.

Go to Cursor Settings → Tools & MCP and click New MCP Server. This opens mcp.json — add the following:

{
  "mcpServers": {
    "janet-ai": {
      "url": "https://mcp.janet.ai/mcp"
    }
  }
}

Save, then back in Cursor Settings click Connect next to janet-ai to authenticate and choose your organization.

Create or edit .vscode/mcp.json in your workspace:

{
  "servers": {
    "janet-ai": {
      "type": "http",
      "url": "https://mcp.janet.ai/mcp"
    }
  }
}

Open the Command Palette and run MCP: List Servers, then start the Janet AI server and complete the OAuth flow.

Open Windsurf Settings and search for MCP. Click View raw config to open mcp_config.json, then add:

{
  "mcpServers": {
    "janet-ai": {
      "serverUrl": "https://mcp.janet.ai/mcp"
    }
  }
}

Save, restart Windsurf, and complete the OAuth flow on first use.

Run this command in your terminal:

codex mcp add janet-ai --url https://mcp.janet.ai/mcp

Then run codex mcp login janet-ai and complete the OAuth flow to connect your workspace.

What You Can Do

Once connected, just talk to your AI agent naturally:

Use case	Example prompt
Find tickets	”Show me my assigned tickets in MAIN”
Search	”Search for tickets about authentication”
Create tickets	”Create a high-priority bug for the login redirect issue”
Schedule tickets	”Schedule a ticket for tomorrow at 9am to review the deployment”
Update tickets	”Move MAIN-452 to In Progress”
Manage sprints	”Add MAIN-100 and MAIN-101 to Sprint 3”
Create objectives	”Create an objective called Q2 Launch with high priority”
Manage objectives	”Add MAIN-100 and MAIN-101 to the Q2 Launch objective”
Add comments	”Add a comment to MAIN-100 saying the fix is deployed”
Attach context	”Add this Slack thread / PR / email / doc to MAIN-123 as context”
Break down work	”Create child tasks on MAIN-200 for each component”
Sort & organize	”Sort the To Do column by priority”
Web search	”What are the best libraries for rate limiting in Node.js?”
Write docs	”Create a document called API Design with the proposed structure”

Available Tools

The MCP server exposes 40 tools that your AI agent discovers and uses automatically.

Workspace

Get user info, organization, projects, statuses, and members.

Get platform documentation and usage guidance.

Tickets

List tickets with optional filters (status, priority, assignee, keyword, dates).

Get full ticket details including description, comments, and child tasks for one or more tickets.

Create one or more tickets in a single call (title, description, status, priority, assignees, labels, sprint, due date, scheduled activation).

Batch update ticket fields (status, priority, assignees, labels, due date).

Soft-delete one or more tickets in a single call. Restorable.

Restore one or more previously deleted tickets together with their child tasks.

Reposition a ticket: top, bottom, at:N, before/after, within kanban, sprint, or objective. Also supports column-wide sort and reorder.

Semantic search across tickets by meaning.

Ticket Context

Attach context to one or more tickets in a single call. The type arg picks the source: slack (permalink or manual reporter+message), discord (permalink or manual username+message), email (sender, subject, body), pull_request (URL), web_link (URL), or document (Janet AI doc by UUID or exact title — idempotent).

List every context item on a ticket (Slack/Discord/email messages, PRs, web links, linked Janet docs, meetings, Google Docs) with its id + short description. Call this before remove_context_from_ticket.

Remove a context item from a ticket by id (id comes from list_ticket_context). Works on any context type.

Child Tasks

List child tasks for a ticket.

Create one or more child tasks on a ticket in a single call.

Batch update child task title, status, priority, or assignee.

Delete one or more child tasks in a single call.

Comments

List comments on a ticket.

Add one or more comments to one or more tickets in a single call.

Batch edit existing comments. Edit history is preserved (the original row is deactivated, a new row inserted with the original created_at).

Delete one or more comments in a single call.

Sprints

List sprints with status, dates, and ticket counts.

Create a new sprint.

Update a sprint’s name, dates, status, or description.

Add tickets to a sprint.

Remove tickets from a sprint.

List tickets in a sprint grouped by status.

Objectives

List objectives with status, priority, and ticket counts.

Create a new objective.

Update an objective’s name, status, priority, or assignees.

Delete an objective.

Add tickets to an objective.

Remove tickets from an objective.

List tickets in an objective grouped by status.

Documents

List documents in the workspace.

Get a document’s full content.

Create a document with title and markdown content.

Update a document’s title or content.

Web

Search the web for current information.

JanetClaw

Post an activity message to the user’s JanetClaw feed for distinct JanetClaw actions (creating a ticket from email, adding context, moving tickets when a PR merges, etc.). Pass ticket_key — click-through URLs resolve automatically.

Activity Log

Every MCP tool call is logged and visible in the MCP page → Usage tab in your dashboard. Organization admins see all members’ calls; members see only their own.

Troubleshooting

Cannot connect / authentication errors

If your client fails to connect, try:

Clear existing auth — In your client, remove and re-add the MCP server to trigger a fresh OAuth flow.
Check your organization — During sign-in, make sure you select the correct organization.
Restart your client — Some clients need a full restart after the OAuth flow completes.

FAQ

What are the rate limits?

The MCP server enforces per-user rate limits. If you hit a 429 Too Many Requests error, wait a minute before retrying. Typical limits are 200 requests/minute and 5,000 requests/hour per user.If you consistently hit rate limits, contact support@janet.ai.

Is there a Janet CLI tool?

mcporter lets you call MCP tools directly as CLI commands — no agent required.First, install it globally:

npm install mcporter

Authenticate once locally:

mcporter auth https://mcp.janet.ai/mcp

Then call any tool directly from the command line:

mcporter call janet-ai.list_tickets --project_key MAIN --status "To Do"

How do I use CLI commands in my cloud-hosted scripts?

First, install it globally and authenticate on your local machine:

npm install mcporter
mcporter auth https://mcp.janet.ai/mcp

Credentials are stored in ~/.mcporter/credentials.json — copy that file’s contents as a secret or environment variable in your cloud environment so scripts can run without an interactive OAuth flow.For example, a Python script that creates a ticket:

import json
import subprocess

subprocess.run([
    "mcporter", "call", "janet-ai.create_tickets",
    "--tickets", json.dumps([{
        "title": "Nightly health check failed",
        "project_key": "MAIN",
        "priority": "High",
    }]),
])

My agent doesn't support the OAuth PKCE flow — how do I connect?

Some agent runtimes support HTTP-based MCP servers but don’t implement the OAuth PKCE flow required by Janet AI (e.g. OpenClaw). You can proxy through mcp-remote to handle auth transparently.First, install it:

npm install -g mcp-remote

Then trigger the OAuth flow in your terminal:

mcp-remote https://mcp.janet.ai/mcp

Then configure your agent to use it:

{
  "mcpServers": {
    "janet-ai": {
      "command": "mcp-remote",
      "args": ["https://mcp.janet.ai/mcp"]
    }
  }
}

mcp-remote runs locally, performs the PKCE handshake with https://mcp.janet.ai/mcp on your behalf, and exposes the server over stdio to your agent. This works with any client that supports stdio-based MCP servers.

Getting started

Project views

Agent Interactions

Ticket Features

Integrations

Setup

What You Can Do

Available Tools

Activity Log

Troubleshooting

Cannot connect / authentication errors

FAQ

​Setup

​What You Can Do

​Available Tools

​Activity Log

​Troubleshooting

​Cannot connect / authentication errors

​FAQ

Setup

What You Can Do

Available Tools

Activity Log

Troubleshooting

Cannot connect / authentication errors

FAQ