"Looking for an MCP to create an issue on Linear" matching MCP servers:

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

Scaffold and audit Starter Series projects — MCP server, Claude Code skill, and CLI in one package.

An MCP server that generates and edits images using OpenAI's GPT Image model, allowing users to create images from text descriptions and edit existing images through natural language.

Enables AI clients to list, retrieve, create, update, and delete tracked issues through MCP tools that call an underlying FastAPI REST API over HTTP. Issue status and priority values are validated, and API or network failures surface as MCP tool errors.

Enables interaction with a local SQLite-backed issue tracker, offering full CRUD operations (search, fetch, summarize, create, comment, close/reopen) with team-scoped visibility, authorization, rate limiting, and audit logging.

Enables agents to keep Linear tickets current by treating the description as the ticket's state and comments as its log, with validated section patches, reconciled drift reporting, whole-ticket reads, typed comments, and a hash-checked claim-then-Done gate. Enforces these rules server-side so they hold across any client, including hands-off labels and refusal of stale or unverified writes.

An MCP server that enables Claude to train a linear regression model by simply uploading a CSV file, handling the entire ML pipeline from data preprocessing to model evaluation.

Custom MCP server for Linear that enables managing issues, projects, and workspaces through natural language, backed by raw GraphQL.

A Model Context Protocol server that enables coding agents to search for and record software issue fixes with semantic search using natural language queries.

A minimal MCP server using FastMCP to demonstrate tool creation, including a get_weather example.

An MCP server that turns CI failures, pull requests, security alerts, and Slack threads into Linear issues, Slack posts, changelogs, docs, and reports with evidence attached, through 25 agent-run workflows over 59 tools spanning GitHub, Linear, Slack, Notion, Google Docs, Google Calendar, Google Sheets, Firecrawl, and Tavily. It also handles credential setup in the OS keychain and pauses for approval before any create, send, change, or delete call.

Bridges the ChatGPT web UI to a local development environment over MCP, letting the model read and patch files, run real shell commands and terminals, execute tests, and control the desktop (screen, mouse, keyboard, clipboard) within user-approved folders. It adds parallel workers, goal/loop long-task control, plugin tools, and a security-hardening layer with risk-tiered shell policy, audit logging, and credential sanitization.

Lets an agent query Linear by writing JavaScript that the server runs in a throwaway worker, exposing schema introspection and a single request helper so only the return value comes back. Runs read-only by default, refusing mutations before any request leaves the process unless explicitly enabled.

Enables AI assistants to manage GitHub issues using deterministic priority scoring and concurrency-safe locking. It supports a structured eight-phase workflow from issue selection through pull request review to ensure consistent prioritization and progress tracking.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Enables ChatGPT to access approved local Windows folders, run commands, control the desktop, and manage session history through a permission-bounded MCP server.

Enables fast, local-only read access to Linear data via the macOS cache, allowing listing, searching, and filtering issues, users, teams, and states without API calls.

Enables agents to convert Markdown into WhatsApp-compatible formatting, including styled text, lists, and tables that fit a phone's monospace width.

MCP server that exposes the OBBBA No Tax on Tips federal deduction logic as callable tools, enabling users to check eligibility and estimate tip deductions.

Enables offline local LLM analysis of text data via MCP, taking raw text and an instruction to return analysis results without cloud calls.