Rize MCP

Live

OAUTH 2.0

PRODUCTIVITY

Productivity

Connect to Rize MCP using OAuth 2.1 with MCP discovery and dynamic client registration. Access and analyze your time tracking data, projects, clients.

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
Rize MCP
agent · Acme Q3
Run
Add Note in Rize MCP
S
rizemcp_add_note
85ms
Rize MCP agent
Add a note about what you're working on. notes give rize context to improve time tracking accuracy. this is the primary.
Sources: Rize MCP
rizemcpmcp
1 tool call
18:29
Message Claude...

Rize MCP tools for AI agents

CALL ANY TOOL
12 tools covering approve, add.
rizemcp_add_note
Add note
Add a note about what you're working on. Notes give Rize context to improve time tracking accuracy. This is the primary way to tell Rize what you worked on. Every call creates a timeline note. If you also provide `blocks` with durations, time entries are created too. **Context only (no entries created):** - "Working on the NVIDIA project today" - "Just finished the pitch deck for Acme" - "Switching to internal tooling" **Context + time entries (blocks with durations):** - "2hrs on NVIDIA pitch deck" → blocks: [{project: "NVIDIA", description: "Pitch deck work", durationMin: 120}] - "30min call with Acme about onboarding" → blocks: [{client: "Acme", description: "Onboarding call", durationMin: 30}] When blocks are provided: defaults to preview mode — shows matched entries for confirmation. Call again with save=true to commit. The tool fetches the user's clients, projects, tasks, existing time entries, app activity, and existing notes for the target date. It detects overlaps between blocks and existing entries.
Parameters
Name
Type
Required
Description
text
string
Required
What did you work on? Natural language.
billable
boolean
Optional
Override billable status for created entries.
blocks
array
Optional
Pre-parsed time blocks. When provided with durations > 0, time entries will be created in addition to the note. Tag each block with any combination of client, project, and/or task.
date
string
Optional
Reference date YYYY-MM-DD. Defaults to today.
save
boolean
Optional
Set true to save time entries after previewing. Only relevant when blocks are provided.
rizemcp_approve_tag_suggestion
Approve tag suggestion
rizemcp_approve_time_entries
Approve time entries
rizemcp_create_client
Create client
rizemcp_create_contract
Create contract
rizemcp_create_label
Create label
rizemcp_create_project
Create project
rizemcp_create_task
Create task
rizemcp_delete_label
Delete label
rizemcp_generate_time_entries
Generate time entries
rizemcp_get_ai_effectiveness_stats
Get ai effectiveness stats
rizemcp_get_contract
Get contract
rizemcp_get_current_user
Get current user
rizemcp_get_login_url
Get login url
rizemcp_get_my_time_tracking_signals
Get my time tracking signals
rizemcp_get_profitability_trend
Get profitability trend
rizemcp_get_team_time_allocation
Get team time allocation
rizemcp_invite_team_member
Invite team member
rizemcp_list_clients
List clients
rizemcp_list_contracts
List contracts
rizemcp_list_my_apps_used
List my apps used
rizemcp_list_my_events
List my events
rizemcp_list_projects
List projects
rizemcp_list_report_runs
List report runs
rizemcp_list_team_members
List team members
rizemcp_reject_time_entries
Reject time entries
rizemcp_update_client
Update client
rizemcp_update_contract
Update contract
rizemcp_update_project
Update project
rizemcp_update_team_member
Update team member

For more tools, view docs.

Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="rizemcp")

mcp = MultiServerMCPClient({
"rizemcp": {
"url": "https://mcp.scalekit.com/rizemcp",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "rizemcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/rizemcp
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "rizemcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/rizemcp
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="rizemcp")
# Connect to MCP at https://mcp.scalekit.com/rizemcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Update an existing time entry?
Copy the prompt
Copied
Create a new Rize account via magic link?
Advanced
Copy the prompt
Copied
Reject pending AI-generated time entry suggestions?
Copy the prompt
Copied
Regenerate AI content for a pending or failed time entry?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
Rize MCP
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Rize MCP
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Rize MCP
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Rize MCP
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other connectors.
Engineering Teams
Engineering standup agent
Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.
Engineering Teams
DevOps assistant agent
Polls GitHub for failing checks and stale PRs, opens Linear issues for the ones that need work, and posts a daily digest to Slack. It acts as the engineer, not a shared service account.
Engineering Teams
Slack triage
Polls Slack for new messages, classifies bugs and support requests with a LangGraph router, files GitHub issues or Zendesk tickets, and confirms in the thread.
People Ops and HR teams
Performance review collector
Collects review feedback from Airtable and Google Forms scoped to each manager's direct reports, writes per-employee summaries to Notion, and DMs the manager a Slack digest.
Test other agents
See the same per-user auth pattern across other connectors.
ENGINEERING
Engineering standup agent
Pull commits from GitHub and GitLab, track Jira issue movement, and post a per-engineer standup brief to Slack.
ENGINEERING
DevOps assistant agent
Poll GitHub for failing checks and stale pull requests, open Linear issues for the ones that need work, and digest to Slack.
ENGINEERING
Slack triage agent
Classify new Slack messages as bugs or support requests, file the GitHub issue or Zendesk ticket, and reply in the thread.
PEOPLE OPS
Performance review collector agent
Collect review feedback from Airtable and Google Forms per manager, summarise each report in Notion, and DM the digest in Slack.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions

Does the agent access Rize as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Rize OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Rize?
Yes. Pass a tool name filter to listScopedTools so the productivity agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Rize.

What happens when a user revokes Rize access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Whose time tracking data can the agent read or approve?
Only the authorizing user's Rize workspace. Time entry approvals, client and contract edits, and notes run as that user, keeping personal productivity data personal.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""rizemcp"": {
""url"": ""https://mcp.scalekit.com/rizemcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.rizemcp]
url = ""https://mcp.scalekit.com/rizemcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""rizemcp"": {
""url"": ""https://mcp.scalekit.com/rizemcp"",
""type"": ""http""
}
}
}