OAUTH 2.0
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.
For more tools, view docs.
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(),
});
.svg)
// 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 ✓
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.
What other MCP connectors does Scalekit support?
Scalekit runs the GitLab MCP server, Vercel MCP server, and Jira MCP server on the same per-user auth, token vault, and audit trail. Browse 500+ connectors in the MCP connector directory.
How do I build a Linear agent?
Follow a step-by-step tutorial: Add Linear Tools to a Claude Agent in 50 Lines of Python; Build a Customer Escalation Agent: Intercom, Linear, Slack; DevOps AI agent assistant for GitHub, Linear, Slack. Each one covers per-user auth, tool scoping, and working agent code for Linear.
.svg)
.jpeg)
