Upstream MCP

Live

BEARER TOKEN

INBOX AUTOMATION

Productivity

Inbox automation in Upstream covers threads, splits, labels, rules, and channels, reached with a bearer token Scalekit vaults per user instead of a shared key.

  • Acts as the user: threads, drafts, and rules resolve against the mailbox of the user who authorized the agent.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: User permissions enforced. 90-day audit trail.
Upstream MCP
agent · Acme Q3
Run
What is sitting in my primary split that I have not replied to?
S
upstreammcp_get_inbox_split_threads
88ms
Inbox agent
6 threads waiting on you. Two are customer escalations older than 24 hours, three are vendor renewals, one is an internal review request.
Sources: 1 split, 6 threads
upstreammcp
6 threads
18:29
Message Claude...

Tools your productivity agent reaches for on Upstream, scoped per user.

CALL ANY TOOL
Inbox automation end to end: read and triage threads, compose and generate drafts, manage splits, labels, rules, channels, and contacts. The token stays vaulted per user.
upstreammcp_compose_thread
Compose thread
Create and send a new email thread. Requires at least one recipient in the "to" field. Optionally assign to channels for team visibility.
Parameters
Name
Type
Required
Description
body
string
Required
Email body (HTML supported)
to
array
Required
Primary recipients (email addresses)
bcc
array
Optional
BCC recipients
cc
array
Optional
CC recipients
channelIds
array
Optional
Channel IDs to assign this thread to (from list-channels)
includeSignatures
boolean
Optional
Whether to append Gmail and Upstream signatures when they are not already present
subject
string
Optional
Email subject line
upstreammcp_create_channel
Create channel
upstreammcp_create_inbox_split
Create inbox split
upstreammcp_create_label
Create label
upstreammcp_delete_inbox_split
Delete inbox split
upstreammcp_done_thread
Done thread
upstreammcp_get_channel_threads
Get channel threads
upstreammcp_get_inbox_split_threads
Get inbox split threads
upstreammcp_get_label_threads
Get label threads
upstreammcp_list_channels
List channels
upstreammcp_list_contacts
List contacts
upstreammcp_list_inbox_splits
List inbox splits
upstreammcp_list_labels
List labels
upstreammcp_list_rules
List rules
upstreammcp_list_sent_threads
List sent threads
upstreammcp_list_snoozed_threads
List snoozed threads
upstreammcp_list_starred_threads
List starred threads
upstreammcp_manage_channel_participants
Manage channel participants
upstreammcp_manage_thread_followers
Manage thread followers
upstreammcp_manage_thread_labels
Manage thread labels
upstreammcp_mark_read
Read mark
upstreammcp_move_to_category
Move to category
upstreammcp_post_thread_comment
Post thread comment
upstreammcp_read_thread
Read thread
upstreammcp_save_draft_reply
Save draft reply
upstreammcp_save_draft_thread
Save draft thread
upstreammcp_search_inbox
Search inbox
upstreammcp_star_threads
Star threads
upstreammcp_update_inbox_split
Update inbox split
upstreammcp_update_rule
Update rule

For more tools, view docs.

Build your Agent
Drop the toolkit in, point it at the user, and your agent can triage threads and draft replies from the first run.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["upstreammcp"], toolNames: ["upstreammcp_list_inbox_splits", "upstreammcp_get_inbox_split_threads", "upstreammcp_compose_thread"] },
pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
name: t.tool.definition.name,
description: t.tool.definition.description,
schema: z.object({}).passthrough(),
func: async (args) => {
const { data } = await sk.tools.executeTool({
toolName: t.tool.definition.name,
identifier: "user_123",
params: args,
});
return JSON.stringify(data);
},
}));

const agent = createReactAgent({ llm, tools: lcTools });
import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["upstreammcp"], toolNames: ["upstreammcp_list_inbox_splits", "upstreammcp_get_inbox_split_threads", "upstreammcp_compose_thread"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
type: "function",
function: {
name: t.tool.definition.name,
description: t.tool.definition.description,
parameters: t.tool.definition.input_schema,
},
}));

const resp = await openai.responses.create({
model: "gpt-4o", input: prompt, tools: llmTools,
});
import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
filter: { connectionNames: ["upstreammcp"], toolNames: ["upstreammcp_list_inbox_splits", "upstreammcp_get_inbox_split_threads", "upstreammcp_compose_thread"] },
pageSize: 100,
});

const llmTools = tools.map((t) => ({
name: t.tool.definition.name,
description: t.tool.definition.description,
input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
model: "claude-sonnet-4-6", max_tokens: 1024,
tools: llmTools,
messages: [{ role: "user", content: prompt }],
});
import { Agent } from "@google/adk/agents";
import {
MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
connectionParams: new StreamableHTTPConnectionParams({
url: "https://mcp.scalekit.com/upstreammcp",
headers: { Authorization: `Bearer ${userScopedToken}` },
}),
});

const agent = new Agent({
name: "agent", model: "gemini-2.0-flash",
tools: await toolset.getTools(),
});
Try these prompts
Paste any prompt into your agent to start running Upstream inbox automation from your workflows.
Triage
Copy the prompt
Copied
What is in my primary split that I have not replied to?
Copy the prompt
Copied
List threads labeled [label] from the last 7 days.
Copy the prompt
Copied
Mark thread [thread_id] as done and tell me what it was about.
Drafting
Copy the prompt
Copied
Generate a draft reply for thread [thread_id] and show it to me first.
Copy the prompt
Copied
Compose a new thread to [email] about the renewal date.
Copy the prompt
Copied
List my unsent drafts.
Automation rules
Copy the prompt
Copied
Create a rule that labels vendor invoices and moves them out of primary.
Copy the prompt
Copied
List existing rules and what each one matches.
Copy the prompt
Copied
Create a split for threads mentioning [keyword].
SEE HOW AUTH WORKS
Your users connect once. Their Upstream MCP credentials stay vaulted, every call is scope-checked, and every action is logged.
1
Authorize
Your user connects
Upstream 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
Upstream 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
Upstream 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
Upstream 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 so attribution, audit, and scope stay accurate.
// shared token
audit → bot_service_account
user_filter → broken

// scalekit
audit → user_abc
scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Upstream MCP today. Others 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 Upstream MCP 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 Upstream MCP bearer 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 Upstream MCP?
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 Upstream MCP.
What happens when a user revokes Upstream MCP 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.
Can the agent send email without me seeing it first?
Only if you expose the send tools. Draft generation is a separate tool from compose and send, so an assistant can be limited to reading and drafting. Every send is scope-checked before the Upstream call and logged against the authorizing user.
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"": {
""upstreammcp"": {
""url"": ""https://mcp.scalekit.com/upstreammcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.upstreammcp]
url = ""https://mcp.scalekit.com/upstreammcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""upstreammcp"": {
""url"": ""https://mcp.scalekit.com/upstreammcp"",
""type"": ""http""
}
}
}