Skip to main content
Glama
tiovikram

Linear MCP Server

by tiovikram

create_issue

Create new issues in Linear with title, description, team assignment, priority, and labels to track and manage project tasks.

Instructions

Create a new issue in Linear

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesIssue title
descriptionNoIssue description (markdown supported)
teamIdYesTeam ID
assigneeIdNoAssignee user ID (optional)
priorityNoPriority (0-4, optional)
labelsNoLabel IDs to apply (optional)

Implementation Reference

  • The handler logic for the 'create_issue' tool. It validates the required title and teamId, calls linearClient.createIssue with the provided arguments, and returns the created issue as JSON text content.
    case "create_issue": {
      const args = request.params.arguments as unknown as CreateIssueArgs;
      if (!args?.title || !args?.teamId) {
        throw new Error("Title and teamId are required");
      }
    
      const issue = await linearClient.createIssue({
        title: args.title,
        description: args.description,
        teamId: args.teamId,
        assigneeId: args.assigneeId,
        priority: args.priority,
        labelIds: args.labels,
      });
    
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(issue, null, 2),
          },
        ],
      };
    }
  • TypeScript type definition for the arguments accepted by the create_issue tool handler.
    type CreateIssueArgs = {
      title: string;
      description?: string;
      teamId: string;
      assigneeId?: string;
      priority?: number;
      labels?: string[];
    };
  • src/index.ts:61-99 (registration)
    Registration of the 'create_issue' tool in the ListTools response, including name, description, and detailed inputSchema matching the handler args.
    {
      name: "create_issue",
      description: "Create a new issue in Linear",
      inputSchema: {
        type: "object",
        properties: {
          title: {
            type: "string",
            description: "Issue title",
          },
          description: {
            type: "string",
            description: "Issue description (markdown supported)",
          },
          teamId: {
            type: "string",
            description: "Team ID",
          },
          assigneeId: {
            type: "string",
            description: "Assignee user ID (optional)",
          },
          priority: {
            type: "number",
            description: "Priority (0-4, optional)",
            minimum: 0,
            maximum: 4,
          },
          labels: {
            type: "array",
            items: {
              type: "string",
            },
            description: "Label IDs to apply (optional)",
          },
        },
        required: ["title", "teamId"],
      },
    },
  • src/index.ts:47-47 (registration)
    Declaration of 'create_issue' tool capability in the server capabilities.
    create_issue: true,
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates an issue but doesn't mention permissions required, whether it's idempotent, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral nuances. For a tool that creates data in Linear, more context is needed to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema, such as formatting examples or constraints. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a new issue') and resource ('in Linear'), which is specific and unambiguous. However, it doesn't differentiate this tool from its sibling 'update_issue' or explain what distinguishes creation from updating, missing full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'update_issue' or 'search_issues'. There's no mention of prerequisites, context, or exclusions, leaving the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tiovikram/linear-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server