bangumi-mcp

bangumi-mcp

MCP server for Bangumi that queries collections, marks anime as watching/watched, and updates per-episode progress via official API, with secure token handling.

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README

bangumi-mcp

Akashic Plugin API v2 插件，用 Bangumi 官方 API 分页查询收藏列表、查询单个条目的准确进度、设置“在看/看过”，并通过章节接口逐集更新动画观看进度。

安全边界

  • 只连接 https://api.bgm.tv，使用官方 Access Token 和符合官方要求的 User-Agent。
  • Access Token 只从 Akashic plugin-data 的 config.local.toml 读取，不写入仓库、日志或工具结果。
  • 所有远端写入先生成包含作品名和目标状态/集数的预览；确认记录单次使用并在 10 分钟后过期。
  • 完整收藏查询或累计读取达到 100 条时，先显示只读查询范围与预计请求数，并等待本轮之后的逐字确认。
  • 动画进度使用 PATCH /v0/users/-/collections/{subject_id}/episodes 和明确的章节 ID，不用条目级 ep_status 修改动画集数。

安装

Akashic 只安装 Git 已提交快照。从 Akashic 仓库执行：

.venv/bin/python main.py plugin-install \
  --source https://github.com/akashic-plugins/bangumi-mcp.git \
  --marketplace github

安装输出会给出数据目录，默认是：

<workspace>/plugin-data/bangumi-github/

登录 Bangumi 后，前往 Bangumi Access Token 页面 生成个人 Token。该 Token 是账号的 API 访问凭据，不是 Bangumi 密码。

在该目录创建权限为 0600 的 config.local.toml：

access_token = "<在此填写 Bangumi Access Token>"
user_agent = "akashic-plugins/bangumi-mcp/0.4.0 (https://github.com/akashic-plugins/bangumi-mcp)"

已安装旧版本的用户如果在本地配置中显式设置了 user_agent，更新插件后也需要将其改为上述新标识。不要把 Token 放进命令行参数或聊天消息。配置完成后检查：

.venv/bin/python main.py plugin-doctor bangumi@github

运行中的 Akashic 会观察配置变化并发布新的 committed generation；新会话会加载 bangumi Skill 和 MCP 工具。

设计文档

开发验证

python -m pip install -r mcp/requirements.txt -r requirements-dev.txt
pytest
PYTHONPATH=/path/to/plugin-contracts \
  python -m akashic_plugin_contracts check plugin.py

单元测试全部使用假的 HTTP 会话，不访问真实 Bangumi 账户，也不需要 Access Token。

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