"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.

A Model Context Protocol server that integrates with Linear, enabling AI assistants to create, update, search, and comment on issues for project management and issue tracking.

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.

A Model Context Protocol server that enables AI assistants to interact with Linear project management systems, allowing users to retrieve, create, and update issues, projects, and teams through natural language.

Enables reading and managing Linear issues by human-readable ID, with tools for searching, creating, updating, commenting, and resolving teams, states, labels, and assignees by name.

Multi-workspace Linear MCP server using Personal API Keys instead of OAuth. Provides tools for managing issues, projects, teams, and more across multiple workspaces.

Enables AI assistants to work with Linear via the Model Context Protocol, covering issue/project management, resource and prompt access, webhooks, and OAuth app setup.

A MCP server that bridges LLMs with GitHub repository management, enabling automated analysis of pull requests, issue management, tag creation, and release management through natural language.

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

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

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

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Enables automatic collection and AI analysis of Slack messages to create organized Notion pages, supporting custom analysis directions like meeting minutes, issue extraction, and topic classification.

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

An autonomous MCP server that uses the Claude Code CLI to solve coding problems without permission prompts.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Provides GDB and clangd-based tools for debugging C++ programs, enabling step execution, variable inspection, diagnostics, and combined runtime-static analysis.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.