Linear

Live

OAUTH 2.0

DEVELOPER TOOLS

Developer Tools

Fast engineering teams run on Linear. Your agent can triage issues, update cycles, and move work forward, scoped to the projects the user has access to.

  • Acts as the user: Issue access and write actions stay tied to the Linear account that 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.
Linear
agent · Acme Q3
Run
What issues are assigned to me and blocking the current cycle?
S
linear_issues_list
64ms
Engineering agent
3 issues assigned to you in the current cycle: ENG-412 (auth refactor, In Progress), ENG-408 (rate limiter, Todo), ENG-401 (webhook retry, In Review).
Sources: 3 issues, ENG cycle 14
linearmcp
3 issues
18:29
Message Claude...

Tools your engineering agent reaches for on Linear, scoped per user.

CALL ANY TOOL
Read issues, manage projects and cycles, update status, and search across the workspace. Same toolkit, every framework, no auth plumbing.
linear_attachment_create
Create attachment
Create an external link attachment on a Linear issue.
Parameters
Name
Type
Required
Description
issueId
string
Required
ID of the issue to attach the link to
title
string
Required
Attachment title
url
string
Required
URL of the attachment
subtitle
string
Optional
Subtitle or description for the attachment
linear_attachment_delete
Delete attachment
linear_attachment_get
Get attachment
linear_attachment_update
Update attachment
linear_attachments_list
List attachments
linear_cycle_archive
Archive cycle
linear_cycle_create
Create cycle
linear_cycle_get
Get cycle
linear_cycle_issues_list
List cycle issues
linear_cycle_update
Update cycle
linear_graphql_query
Query graphql
linear_issue_delete
Delete issue
linear_issue_relation_create
Create issue relation
linear_issue_search
Search issue
linear_issue_unarchive
Issue unarchive
linear_issues_list
List issues
linear_label_archive
Archive label
linear_label_get
Get label
linear_label_update
Update label
linear_project_create
Create project
linear_project_delete
Delete project
linear_project_milestones_list
List project milestones
linear_project_update
Update project
linear_team_create
Create team
linear_team_delete
Delete team
linear_team_get
Get team
linear_teams_list
List teams
linear_users_list
List users
linear_viewer_get
Get viewer
linear_webhook_update
Update webhook

For more tools, view docs.

Build your Agent
Drop the toolkit in, point it at the user, and your agent can list Linear issues, create tickets, and update status 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: ["linear"], toolNames: ["linear_issues_list", "linear_search_issues", "linear_issue_create"] },
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: ["linear"], toolNames: ["linear_issues_list", "linear_search_issues", "linear_issue_create"] },
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: ["linear"], toolNames: ["linear_issues_list", "linear_search_issues", "linear_issue_create"] },
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/linear",
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 managing Linear workflows.
Search & recall
Copy the prompt
Copied
List all open issues assigned to me in [team].
Copy the prompt
Copied
What issues are In Progress in the current cycle?
Copy the prompt
Copied
Find all bugs labeled [critical] in [team].
Copy the prompt
Copied
What issues are in [project name]?
Action & creation
Copy the prompt
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Create an issue in [team]: [title] — [description], priority High.
Copy the prompt
Copied
Move issue [ENG-123] to In Progress.
Copy the prompt
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Assign [ENG-456] to [person name].
Copy the prompt
Copied
Add label [backend] to issue [ENG-789].
Cycles & projects
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What is in the current cycle for [team]?
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List all issues not yet started in the current cycle.
Copy the prompt
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How many open issues are there by priority in [team]?
Copy the prompt
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What projects are active in [team] right now?
SEE HOW AUTH WORKS
Users authorize Linear once. Their workspace credentials stay vaulted, every call is checked, and every action is logged.
1
Authorize
Your user connects
Linear
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
Linear
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
Linear
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
Linear
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
Same per-user auth pattern across other engineering agents and MCP connectors. Working code, live demos, fork what fits.
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.
Engineering Teams
Auto release notes agent
Reads merged GitHub PRs, groups them into structured release notes, publishes the page to Notion, and announces the release in Slack. Every call runs on the engineer's own delegated OAuth.
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.
Test other agents
Same per-user auth pattern across other engineering agents and MCP connectors. Working code, live demos, fork what fits.
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
Engineering standup agent
Pull commits from GitHub and GitLab, track Jira issue movement, and post a per-engineer standup brief 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.
ENGINEERING
Auto-release notes agent
Group merged GitHub PRs into structured release notes, publish the page to Notion, and announce the release in Slack.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Issue changes lose team attribution
A shared Linear token looks fine in a demo. In production, every issue assignment, status update, and cycle change logs as the integration. Team attribution breaks. Per-engineer workload metrics break. Scalekit resolves the actual user's credential, so Linear tracks ownership and throughput correctly.
// shared bot token
token = "sk_linear_shared_xxx"
audit → bot_service_account
user_filter → broken

// scalekit · per-user
token = resolve(user_id)
audit → user_abc
scope → enforced ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Linear today. Jira, GitHub, GitLab 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 Linear 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 Linear oauth 2.0 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 Linear?
Yes. Pass a tool name filter to listScopedTools so the engineering agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Linear.

What happens when a user revokes Linear 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 work across multiple Linear workspaces?
One workspace per connected account. Per-user, per-workspace namespacing in the vault. A user can authorize multiple workspaces; cross-workspace access is denied by default.

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"": {
""linear"": {
""url"": ""https://mcp.scalekit.com/linear"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.linear]
url = ""https://mcp.scalekit.com/linear""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""linear"": {
""url"": ""https://mcp.scalekit.com/linear"",
""type"": ""http""
}
}
}