mcp-linear

mcp-linear

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.

Category
访问服务器

README

mcp-linear

MCP server exposing Linear issue operations. Standalone — no dependency on the built-in Claude Linear MCP.

Issues are addressed by their human identifier (GOV-123). States, teams, labels, and assignees are given by name; the server resolves them to Linear UUIDs and returns an error listing valid options when a name does not match.

Tools

Tool Description
get_issue Fetch an issue by identifier
list_my_issues Issues assigned to the API key's owner
search_issues Full-text search with team/state/assignee filters
create_issue Create an issue on a team
update_issue Update fields on an existing issue
get_comments Comments on an issue
add_comment Post a comment
list_teams Team keys and names
list_states Workflow states for a team
list_labels Labels on a team plus workspace labels (team optional)
list_users Active users

Setup

python3 -m venv .venv
.venv/bin/pip install -e ".[dev]"
cp .env.example .env
# Edit .env — set LINEAR_API_KEY

Get an API key: Linear → Settings → Security & access → Personal API keys. Write operations need a key with write access.

Add to Claude Code

{
  "mcpServers": {
    "linear": {
      "command": "/Users/piuschungath/Workspace/mcp-linear/.venv/bin/mcp-linear",
      "env": { "LINEAR_API_KEY": "lin_api_..." }
    }
  }
}

Tests

.venv/bin/pytest

All HTTP is mocked with respx. No API key and no network access are needed.

With mcp-pr-assistant

The two servers compose without importing each other: fetch a ticket with get_issue, pass its fields to create_pr_from_ticket, then post the PR URL back with add_comment.

Schema verification

The GraphQL field names in src/mcp_linear/queries.py were verified against the live Linear API on 2026-08-21, by running the tools' actual query strings (not copies of them) against a real workspace.

Verified correct:

  • the Float! issue-number comparator
  • team-scoped labels via team { labels }
  • the root issueLabels connection
  • viewer.assignedIssues(orderBy: updatedAt)
  • every field the three mutations send — IssueCreateInput, IssueUpdateInput and CommentCreateInput all accept teamId, title, description, stateId, assigneeId, priority, labelIds, issueId and body as used

One divergence was found and fixed:

  • Full-text search. issueSearch rejects its query argument as deprecated. Search now uses searchIssues(term: ...), which returns IssueSearchPayload whose nodes are IssueSearchResult, not Issue — so it cannot spread the IssueFields fragment. queries.py declares a second fragment, SearchFields, with the identical selection on that type. Introspection confirmed IssueSearchResult carries every field IssueFields selects. If you change one fragment, change the other.

One thing remains unconfirmed:

  • Workspace labels. The root issueLabels connection resolves, but whether it returns workspace-wide labels only — or also team-scoped labels belonging to other teams — was not established. Label resolution consults a team's own labels first, so a team label always wins over a same-named workspace one.

To re-verify after a Linear schema change:

LINEAR_API_KEY=lin_api_... .venv/bin/python scripts/probe_schema.py <team-key> <issue-number> <issue-uuid>

It takes a team key, an existing issue number on that team, and that issue's UUID (and prompts once, interactively, for a team UUID printed by its first probe). The probe is read-only: the mutations are checked by introspecting their input types, never by writing to your tracker.

Notes

  • Linear personal API keys are sent as Authorization: <key> with no Bearer prefix.
  • Linear reports most failures as HTTP 200 with a top-level errors array, so the client checks the response body rather than the status code.
  • Team, state, label, and user metadata is cached for the lifetime of the server process. Restart the server after changing a team's workflow states or labels.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选