Linear Issues▌
by keegancsmith
Linear Issues integrates with Linear to give you read-only access to issue details and comments without switching apps.
Integrates with Linear issue tracking to provide read-only access to issue details and comments without switching contexts.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers reviewing issues during coding sessions
- / Project managers checking issue status quickly
- / Teams discussing Linear issues in AI conversations
capabilities
- / Fetch Linear issue details by URL or identifier
- / Retrieve complete issue information with all comments
- / Access Linear data without leaving your AI conversation
- / Query issue status and metadata
what it does
Provides read-only access to Linear issues and comments directly from your AI assistant without switching apps or browser tabs.
about
Linear Issues is a community-built MCP server published by keegancsmith that provides AI assistants with tools and capabilities via the Model Context Protocol. Linear Issues integrates with Linear to give you read-only access to issue details and comments without switching apps. It is categorized under productivity.
how to install
You can install Linear Issues in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Linear Issues is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Linear Issues MCP Server
This is a simple MCP (Model Context Protocol) server that provides read-only access to Linear issues. It allows language models to fetch Linear issues and their associated data using a Linear API token.
Features
The server provides two tools:
linear_get_issue: Fetches basic details about a Linear issue by URL or identifierlinear_get_issue_with_comments: Fetches complete information about a Linear issue including all comments
Requirements
- Node.js
- A Linear API token or OAuth access token
Installation
No installation is needed if you use npx. Just make sure you have Node.js and npm installed.
Getting a Linear API Token
You can obtain a Linear API token in two ways:
-
API Key (simplest): Generate an API key in your Linear API settings
-
OAuth Token: For more advanced use cases or user-specific access
- Create an OAuth2 application in Linear
- Follow the OAuth flow to get a user access token
Usage with Claude for Desktop
To use this MCP server with Claude for Desktop:
-
Make sure you have your Linear API token ready
-
Add the server to your Claude for Desktop configuration at:
- MacOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json - Windows:
%AppData%\Claude\claude_desktop_config.json
- MacOS:
Example configuration:
{
"mcpServers": {
"linear-issues": {
"command": "npx",
"args": ["-y", "@keegancsmith/linear-issues-mcp-server"],
"env": {
"LINEAR_API_TOKEN": "your_linear_api_token_here"
}
}
}
}
- Restart Claude for Desktop
Example Usage
Once the server is set up, you can use it in Claude to interact with Linear issues:
Can you get me the details for issue ENG-123?
Claude will use the linear_get_issue tool with your issue ID, accessing the token from environment variables.
What are all the comments on the issue at https://linear.app/company/issue/ENG-123/issue-title?
Claude can use linear_get_issue_with_comments to fetch the full issue details including comments.
License
MIT
FAQ
- What is the Linear Issues MCP server?
- Linear Issues is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Linear Issues?
- This profile displays 73 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
List & Promote Your MCP Server
Share your MCP server with the developer community
Ratings
4.7★★★★★73 reviews- ★★★★★Shikha Mishra· Dec 28, 2024
I recommend Linear Issues for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Tariq Choi· Dec 28, 2024
Linear Issues is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Tariq Abebe· Dec 28, 2024
Linear Issues has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Kofi Perez· Dec 16, 2024
According to our notes, Linear Issues benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Yusuf Reddy· Dec 12, 2024
Useful MCP listing: Linear Issues is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Daniel Jain· Dec 12, 2024
Linear Issues is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Xiao Bhatia· Dec 8, 2024
Strong directory entry: Linear Issues surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Isabella Khanna· Dec 4, 2024
Strong directory entry: Linear Issues surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ira Agarwal· Dec 4, 2024
I recommend Linear Issues for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Diya Thompson· Nov 23, 2024
Linear Issues is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
showing 1-10 of 73