MCP server for 0Latency — persistent memory layer for AI agents. Give Claude, Cursor, or any MCP client long-term memory.
Free
Nothing to run from here
Getnote is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
Open Installation—
p95 latency
—
call success
local
runs on your machine
—
calls last 7d
What it does
MCP server for 得到大脑（Get笔记） — manage notes and knowledge bases from AI assistants
Quickstart
# 1 — run it from where its publisher ships it
npx -y @getnote/mcp
# 2 — ask your agent something
> MCP server for 得到大脑（Get笔记） — manage notes and knowledge bases from AI assistants
Getnote is free: there is no plan to choose, no cap to set and nothing that can bill you.
Publishernot claimed
GEAll 1 server
@getnote1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Getnote as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. It is scanned, signed and pinned to the version you choose — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. Claude Code registers it in one command.
claude mcp add getnote-mcp -- npx -y @getnote/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free to install, and it runs from its publisher’s own package: no account, no key, no card.
What it writes
One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
38 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
获取笔记列表（每次固定返回 20 条，服务端不支持 limit 参数）。用游标翻页：首次请求不传 cursor；后续把上一次响应返回的 cursor 字段原样传入，直到 has_more 为 false。响应里的 total 是全库笔记总数，不是本页条数。
Takes no parameters.
Example callreturns →
获取指定笔记的详细内容，包括正文、标签、附件、音频转录、网页链接等。\n\n**字段语义说明（AI Agent 重要参考）**：\n
Takes no parameters.
Example callreturns →
直接读取笔记原文。链接笔记返回网页原文，录音笔记返回转写原文，文字笔记返回正文；不要把 AI 摘要冒充原文。
Takes no parameters.
Example callreturns →
直接读取录音、会议或课堂笔记的转写原文；没有转写时明确返回不可用。
Takes no parameters.
Example callreturns →
直接列出笔记中的图片、音频和文件附件，不需要从完整详情中猜字段。
Takes no parameters.
Example callreturns →
直接读取录音或会议笔记的结构化时间线和原文资源；没有时间线时明确返回不可用。
Takes no parameters.
Example callreturns →
直接读取录音笔记的快捷笔记；没有快捷笔记时明确返回不可用。
Takes no parameters.
Example callreturns →
读取从会议总结中明确的待办章节按规则解析出的条目。返回 source 和 items；空列表表示未识别到明确待办章节，不应让模型自由补写。
Takes no parameters.
Example callreturns →
新建笔记（⚠️ 仅支持新建，不支持编辑已有笔记）。支持纯文本笔记（plain_text）、链接笔记（link）和图片笔记（img_text）。\n\n🔗 **笔记内链**：Get笔记正文支持链接到其他笔记，格式为
Takes no parameters.
Example callreturns →
查询创建笔记任务的处理进度。用于链接笔记（note_type=link）创建后，通过 save_note 返回的 task_id 轮询任务状态，直到 status 变为 success（可获取 note_id）或 failed（可获取 error_msg）。建议每 10~30 秒轮询一次，约 3 分钟内完成。需要 note.content.read scope。
Takes no parameters.
Example callreturns →
删除笔记（移入回收站）。需要 note.content.trash scope。
Takes no parameters.
Example callreturns →
更新已有笔记的标题、内容或标签。⚠️ 仅支持 plain_text 类型笔记，链接笔记、图片笔记等暂不支持更新。至少需要传 title、content、tags 中的一个。tags 是替换操作，会覆盖原有标签。
Takes no parameters.
Example callreturns →
为指定笔记添加标签。
Takes no parameters.
Example callreturns →
删除笔记的指定标签（系统标签不可删除）。
Takes no parameters.
Example callreturns →
获取用户创建、拥有或加入的知识库列表，包含普通、书籍、客户档案和团队知识库（TEAMSPACE）。返回 topics[]、has_more、total；保存前可按 name/scope 选择 topic_id。
Takes no parameters.
Example callreturns →
创建新的知识库。⚠️ 限制：每天最多创建 50 个知识库，北京时间自然日 00:00 重置。
Takes no parameters.
Example callreturns →
获取指定知识库内的笔记列表（每页 20 条）。\n\n**AI Agent 提示**：列表返回的
Takes no parameters.
Example callreturns →
批量将笔记添加到知识库（每批最多 20 个）。
Takes no parameters.
Example callreturns →
浏览知识库文件夹结构及当前目录下的笔记等资源。支持个人、书籍、客户档案和团队知识库。
Takes no parameters.
Example callreturns →
在知识库中创建文件夹。
Takes no parameters.
Example callreturns →
重命名或移动知识库文件夹。未提供的字段保持不变。
Takes no parameters.
Example callreturns →
删除空的知识库文件夹。属于破坏性操作，调用前必须取得用户确认。
Takes no parameters.
Example callreturns →
将笔记从知识库中移除。
Takes no parameters.
Example callreturns →
获取图片上传配置，包括支持的文件类型、大小限制等。上传图片前先调用此接口了解约束。
Takes no parameters.
Example callreturns →
获取 OSS 图片上传凭证。返回 accessid/host/policy/signature 等字段，用于 multipart/form-data POST 上传图片到阿里云 OSS。上传成功后获取 image_id，再用 save_note 创建图片笔记。⚠️ mime_type 必须与实际文件格式一致，否则 OSS 签名失败。
Takes no parameters.
Example callreturns →
上传图片到 OSS。返回 image_url（用于创建图片笔记的 image_urls 参数）。
Takes no parameters.
Example callreturns →
获取知识库订阅的博主列表。需要 topic.blogger.read scope。
Takes no parameters.
Example callreturns →
把抖音博主订阅到指定知识库，后续可读取该博主内容。
Takes no parameters.
Example callreturns →
获取知识库中某个博主发布的内容列表（摘要，不含原文）。需要 topic.blogger.read scope。
Takes no parameters.
Example callreturns →
获取博主内容详情，包含完整原文（post_media_text）。需要 topic.blogger.read scope。
Takes no parameters.
Example callreturns →
获取知识库中已完成且 AI 已处理的直播列表。需要 topic.live.read scope。
Takes no parameters.
Example callreturns →
获取直播详情，包含 AI 摘要（post_summary）和完整原文转写（post_media_text）。需要 topic.live.read scope。
Takes no parameters.
Example callreturns →
订阅一个得到 App 直播到知识库。直播结束后经 AI 处理即可通过 list_topic_lives 查看。目前仅支持得到 App 直播链接。需要 topic.live.write scope。
Takes no parameters.
Example callreturns →
生成笔记的公开分享链接。幂等接口，多次调用返回同一个 share_url。需要 note.sharing.write scope。
Takes no parameters.
Example callreturns →
获取当前用户订阅的知识库列表（他人公开的，非自己创建）。返回 topics[]、has_more、total。
Takes no parameters.
Example callreturns →
查询当前 API Key 的调用配额，包括 read/write/write_note 三类的日/月剩余次数。
Takes no parameters.
Example callreturns →
全局语义搜索：在所有笔记中进行语义召回。适用场景：「搜一下」「找找我哪些笔记提到了 XX」。返回结果按相关度从高到低排序。需要 note.recall.read scope。
Takes no parameters.
Example callreturns →
知识库语义搜索：在指定知识库范围内进行语义召回。适用场景：「在我的 XX 知识库搜一下 XX」。返回结果按相关度从高到低排序。需要 note.topic.recall.read scope。
Takes no parameters.
Example callreturns →
Freeyour plan
$0 forever
- Every tool, no call limit
- No card, no account needed
- Source published under a licence you can read
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because nothing bills
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable. Getnote costs nothing to install and nothing to call, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: $8.42
$16.58 left
ATrust score 98 / 100
Release 1.7.0 · scanned 25 Aug 2026
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
Threat score100
Client score98
Findings1 threat · 0 capability
Capabilityminimal
Coveragesource
Verificationnone
Surface digest1036efef10c9f8a0c24989208b359607481d6ee60e66888d103940eebe1d1772
Score vectorthreat 100 → client 98
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| verification-discount | none | publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read | −2 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (38 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| list_notes | no tags | |
| get_note | no tags | |
| get_note_original | no tags | |
| get_note_transcript | no tags | |
| get_note_attachments | no tags | |
| get_note_timeline | no tags | |
| get_note_quick_note | no tags | |
| get_note_todos | no tags | |
| save_note | no tags | |
| get_note_task_progress | no tags | |
| delete_note | no tags | |
| update_note | no tags | |
| add_note_tags | no tags | |
| delete_note_tag | no tags | |
| list_topics | no tags | |
| create_topic | no tags | |
| list_topic_notes | no tags | |
| batch_add_notes_to_topic | no tags | |
| list_topic_directories | no tags | |
| create_topic_directory | no tags | |
| update_topic_directory | no tags | |
| delete_topic_directory | no tags | |
| remove_note_from_topic | no tags | |
| get_upload_config | no tags | |
| get_upload_token | no tags | |
| upload_image | no tags | |
| list_topic_bloggers | no tags | |
| follow_topic_blogger | no tags | |
| list_topic_blogger_contents | no tags | |
| get_blogger_content_detail | no tags | |
| list_topic_lives | no tags | |
| get_live_detail | no tags | |
| follow_topic_live | no tags | |
| share_note | no tags | |
| list_subscribe_topics | no tags | |
| get_quota | no tags | |
| recall | no tags | |
| recall_knowledge | no tags |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
Integrityfirst-seen
Surface digest1036efef10c9f8a0
Scanned2026-08-25
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Pinned to 1.7.0 — the install command below asks for that release. A pin is part of an install, so it is kept for this visit and written down when you install.
1.7.0
undated
installedNo release note was published with this version.
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no reviews yet
Reviews are earned
Only accounts with at least 50 real tool calls against this server in the last 90 days can post. Ratings are weighted by how much the reviewer actually uses it, and publishers can reply once per review.
Reviews are earned
Writing one takes an account with at least 50 real tool calls against Getnote in the last 90 days. That is the whole gate — there is no other way to post, which is why the counts beside each review are worth reading.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes an account with 50 real tool calls against it.