A
licenseNot graded
qualityC
maintenanceMCP server for AI agents to read, write, and organize notes in a local-first, human-in-the-loop note-taking app.
5 npm
2
MIT
hedgedoc-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@hedgedoc-mcpCreate a new note with the title 'Meeting Notes' and content 'Discuss Q3 goals'."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
hedgedoc-mcp
An MCP server that lets AI agents — Claude Code, Codex, Cursor, VS Code, OpenCode, Pi, or any other MCP client — read and write notes on a self-hosted HedgeDoc 1.x instance.
HedgeDoc 1.x has no API token system, so this server handles the real auth model (session cookies from email/password login) and exposes it as a clean, agent-friendly toolset.
Why this exists
HedgeDoc is a great self-hosted, open-source, collaborative markdown editor. But if you want an AI agent to write notes to it programmatically, you hit a wall immediately: HedgeDoc 1.x has no API tokens. Every write endpoint (POST /new, etc.) requires an authenticated browser-style session, tracked via the Express session cookie configured by the instance (normally connect.sid).
This project does the unglamorous work of handling that correctly — login, cookie storage, automatic re-authentication on expiry — and wraps it in an MCP server so any agent can just call hedgedoc_create_note and not think about any of it.
Related MCP server: Joplin Server MCP
Features
🔐 Handles HedgeDoc 1.x's real auth model (session cookies, not tokens)
🔁 Auto re-login on session expiry — no manual cookie refresh needed
🛠️ 5 MCP tools: create, read, info, whoami, history
🐍 Standalone Python client (
hedgedoc_mcp.client.HedgeDocClient) usable outside MCP too✅ Fully tested — against an in-process fake HedgeDoc server; no live instance required
📦 Works with any MCP client — setup guides for 20+ agents: Claude Code, Codex, Cursor, VS Code, OpenCode, Pi, Gemini CLI, Goose, Zed, and more
Quick start
1. Install uv
Your agent starts the server for you with uvx, which downloads and caches hedgedoc-mcp from PyPI on first use. You only need uv installed:
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS / Linux
# Windows: powershell -c "irm https://astral.sh/uv/install.ps1 | iex"You don't run uvx hedgedoc-mcp yourself: it's a stdio server, so it just waits for an agent to talk to it.
uv tool install hedgedoc-mcp # persistent install; point your agent at the `hedgedoc-mcp` executable
pip install hedgedoc-mcp # into an existing environment
# Unreleased changes from the main branch:
uvx --from git+https://github.com/mrsunglasses-experiments/hedgedoc-mcp hedgedoc-mcp2. Choose your credentials
The server is configured entirely through environment variables:
Variable | Required | Description |
| Yes | Your instance's URL as shown in the browser, e.g. |
| One of these two options | Email/password login. The server logs in on first use and again whenever the session expires. |
| One of these two options | A session cookie from |
| No | Only if your instance uses a session cookie name other than |
Recommended: set HEDGEDOC_EMAIL and HEDGEDOC_PASSWORD. That's all you need, and you never have to refresh anything. Email login must be enabled on the instance (CMD_EMAIL=true, the default).
Set these in your agent's MCP config (step 3), not just in your shell. Most agents start MCP servers with a minimal environment, so variables you export usually don't reach the server.
uvx --from hedgedoc-mcp hedgedoc-mcp-login --url https://md.example.com --email you@example.comIt prompts for your password (or reads HEDGEDOC_PASSWORD; avoid --password, which lands in your shell history) and prints HEDGEDOC_SESSION_COOKIE=... for your agent's config. With --write-env .env, it also saves the value to a file readable only by you. The server doesn't read .env files itself.
3. Connect your agent
For Claude Code:
claude mcp add hedgedoc --scope user \
-e HEDGEDOC_URL=https://md.example.com \
-e HEDGEDOC_EMAIL=you@example.com \
-e HEDGEDOC_PASSWORD='your-password' \
-- uvx hedgedoc-mcpMost other agents take the same three pieces of information: command uvx, argument hedgedoc-mcp, and the environment variables above. Config files and formats differ, though. docs/CLIENTS.md has a ready-to-paste config for each of these clients:
Terminal agents | Claude Code · Codex CLI · Gemini CLI · GitHub Copilot CLI · OpenCode · Pi · Amp · Goose · Crush · Hermes Agent · Factory Droid · Qwen Code · Devin CLI |
Editors and IDEs | Cursor · VS Code (Copilot) · Devin Desktop (Windsurf) · Zed · JetBrains · Cline · Kilo Code · Continue · Kiro |
Desktop apps |
The guide also covers keeping passwords out of config files that get committed, plus troubleshooting.
4. Try it
Ask your agent something like "Create a HedgeDoc note summarizing this conversation" or "Which HedgeDoc account are you logged in as?". If the tools don't show up, check the setup with MCP Inspector, which runs the server outside any agent.
Available tools
Tool | Description |
| Create a new note (optionally with a custom URL alias). Returns the note ID and URL. |
| Fetch a note's raw markdown content by ID or alias. |
| Get a note's title, description, view count, and timestamps. |
| Verify the session is valid and show the logged-in user. |
| List the logged-in user's recently viewed/pinned notes. |
There is no update tool: HedgeDoc 1.x has no HTTP endpoint for editing a note (see Known limitations), so write a note's full content when creating it.
Using the Python client directly
You don't need MCP to use this — the underlying client is a normal Python class:
from hedgedoc_mcp.client import HedgeDocClient
client = HedgeDocClient("https://md.example.com")
client.login(email="you@example.com", password="your-password")
result = client.create_note("# Research notes\n\nSome findings...")
print(result.url)
content = client.read_note(result.note_id)
info = client.note_info(result.note_id)Known limitations
HedgeDoc 1.x's HTTP API is genuinely limited compared to newer forks — see docs/LIMITATIONS.md for the full rundown, including:
No API tokens (session-cookie auth only)
No HTTP note-update endpoint
No delete endpoint over HTTP
These are constraints of the HedgeDoc 1.x server itself, not this client — the docs explain the workarounds this project uses and what genuinely isn't possible.
Development
git clone https://github.com/mrsunglasses-experiments/hedgedoc-mcp.git
cd hedgedoc-mcp
uv venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest # run tests (against an in-process fake HedgeDoc; no live server needed)
ruff check . # lint
ruff format --check . # formattingSee docs/ARCHITECTURE.md for how the auth flow and MCP layer fit together, and CONTRIBUTING.md for contribution guidelines.
License
MIT — see LICENSE.
Available Tools
6 toolshedgedoc_create_noteA
Create a new note on the HedgeDoc instance. Returns JSON with two fields: 'note_id' (the unique identifier / URL slug) and 'url' (the full URL where the note can be viewed or shared). Use alias to assign a human-readable slug such as 'q3-research-notes' — alias-based notes can later be overwritten with hedgedoc_update_note. Notes created without an alias get a random ID and cannot be updated over HTTP. Alias support requires FreeURL mode enabled on the server (CMD_ALLOW_FREEURL=true).
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| alias | No | Optional custom URL slug, e.g. 'meeting-2026-08-16' or 'q3-research'. Must be URL-safe (letters, digits, hyphens). Required if you intend to update this note later. Requires FreeURL mode on the server. | |
| content | Yes | Full markdown content for the note. Supports standard CommonMark plus HedgeDoc extensions (diagrams, math, front matter, etc.). |
TDQS
A4.9/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the JSON return shape, the consequence of omitting alias (random ID, cannot be updated), and the server requirement (CMD_ALLOW_FREEURL=true). This is rich behavioral context beyond a mere 'create' statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, front-loaded with purpose and return info, then essential caveats. No redundant statements; every sentence contributes critical usage or behavioral detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter create tool with no output schema or annotations, the description fully covers purpose, return format, parameter semantics, limitations, and prerequisites. It is complete and self-sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing baseline 3. The description adds meaning beyond the schema by explaining the strategic implications of the alias parameter (update capability) and the FreeURL dependency, while content is straightforward.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Create a new note on the HedgeDoc instance,' a specific verb+resource. It elaborates with return fields and differentiates from hedgedoc_update_note by explaining that alias-based notes can be overwritten while alias-less notes cannot be updated over HTTP.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use an alias ('if you intend to update this note later') and explicitly names the alternative tool (hedgedoc_update_note). It also discloses the server prerequisite (FreeURL mode), giving the agent clear criteria for effective use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hedgedoc_list_historyA
List the logged-in user's recently viewed and pinned notes. Returns a JSON array of note objects. Each object includes: 'id' (note ID or alias), 'text' (note title), 'tags' (array of strings), 'pinned' (boolean), and 'time' (last-viewed timestamp in milliseconds). Requires a valid session — will raise an error if not authenticated.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
A4.3/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the auth requirement and error condition ('requires a valid session — will raise an error if not authenticated') and describes the return format in detail. It does not explicitly state read-only, but 'list' implies it. This is strong transparency for a simple read tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose, second covers return format and auth. Front-loaded and efficient with zero wasted words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless list tool with no output schema, the description covers purpose, return structure, and authentication requirements. It is complete enough for an agent to select and invoke correctly without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema provides no information. The description does not need to explain parameters. Baseline for 0 params is 4, and the description adds value by detailing the output fields, which is acceptable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List the logged-in user's recently viewed and pinned notes', using a specific verb and resource. It is distinct from sibling tools like create/read/update/note_info/whoami, as it focuses on history.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving recently viewed and pinned notes but does not explicitly contrast it with alternatives or state when not to use it. No exclusions are mentioned, but the purpose is clear enough to imply when it is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hedgedoc_note_infoA
Get metadata for a note. Returns JSON with: 'title' (string), 'description' (string or null), 'viewcount' (integer — total views), 'createtime' and 'updatetime' (ISO 8601 timestamps, e.g. '2026-08-16T10:30:00.000Z'). This is a public endpoint — no authentication required.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| note_id | Yes | Note ID or alias. |
TDQS
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return JSON structure with types and ISO timestamp format, and states it requires no authentication. However, it does not explicitly confirm zero side effects, though 'Get' implies read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a compact three sentences: purpose, return format, and auth requirement. Every sentence conveys necessary information without redundancy, earning a maximum.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple single-parameter nature and absence of an output schema, the description generously covers what is returned. It also notes the public accessibility, leaving little ambiguity for an agent deciding to invoke it. The tool is simple enough that this is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the only parameter 'note_id' as 'Note ID or alias.' The description adds no additional meaning about the parameter, such as format or examples, so baseline 3 applies given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get metadata') and clarifies the resource ('a note'). It also enumerates the exact fields returned, distinguishing it from sibling tools like hedgedoc_read_note which presumably returns content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool over alternatives, such as hedgedoc_read_note for content. It implies usage by focusing on metadata but offers no direct comparison or exclusions. The public endpoint note provides context about authentication but not when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hedgedoc_read_noteA
Fetch the raw markdown content of an existing note by its ID or alias. Returns the note's markdown as a plain string. This is a public endpoint — no authentication is required to read notes on instances that allow public access.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| note_id | Yes | The note's unique ID (e.g. 'AbC123XyZ') or custom alias (e.g. 'my-meeting-notes'). Both forms are accepted. |
TDQS
A4/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the return type ('markdown as a plain string'), authentication requirements, and that it is a public access point. It does not mention error handling or rate limits, but for a simple read operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, each contributing unique information: the action, the return format, and the access control context. There is no repetition or filler, making it well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single param, no output schema, no annotations), the description provides sufficient context: what it returns, how the ID is specified, and the public access nature. It could mention error cases or note existence, but overall it is complete for a straightforward read endpoint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the sole parameter (note_id) with examples of both ID and alias forms. The description adds no extra semantic depth for the parameter itself, so the schema's high coverage sets the baseline at 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch the raw markdown content'), the resource ('existing note'), and the identifier types ('by its ID or alias'). It distinguishes itself from sibling tools like create_note and update_note by focusing on read-only content retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides useful context about being a public endpoint with no authentication required, which informs when it can be used. However, it does not explicitly mention alternatives or when to use this tool over others like note_info or list_history, so the guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hedgedoc_update_noteA
Overwrite the entire content of an existing note. IMPORTANT: this only works for notes that were originally created with a custom alias (via hedgedoc_create_note's alias parameter). HedgeDoc 1.x has no REST update endpoint for random-ID notes — those can only be edited live in the browser. If the target note was created without an alias, this call will fail. The update is a full overwrite — partial/patch updates are not supported.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | New full markdown content. Replaces the note's current content entirely. | |
| note_id | Yes | The custom alias of the note to overwrite (e.g. 'my-meeting-notes'). Random-ID notes cannot be updated over HTTP. |
TDQS
A4.3/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the destructive nature of full overwrite, the alias-only constraint, and failure mode for random-ID notes. It does not mention authentication or response semantics, but for a simple update operation, the key behavioral traits are well covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main action, then follows with necessary caveats. The IMPORTANT notice is somewhat lengthy but each sentence provides essential warning information. It could be tightened slightly, but it's well-structured for a mutation tool with significant constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (alias-only update, full overwrite), the description covers the critical constraints and failure modes. There is no output schema, and the description doesn't explain the response shape, but that's not a major gap for a straightforward update. The main usage scenarios and pitfalls are clearly communicated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description reinforces that note_id must be a custom alias and that content replaces the entire note, but it largely restates what is already in the schema descriptions, adding minimal extra semantic value beyond the structured fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Overwrite the entire content of an existing note.' It identifies the specific resource (note) and the action (full overwrite), and distinguishes itself from sibling tools like create, read, and info by specifying this is an update operation with full-content replacement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage guidance is explicit: it specifies that this only works for notes created with a custom alias, and that random-ID notes cannot be updated via HTTP. It also states the call will fail for non-alias notes and that partial updates are not supported, giving clear when-to-use and when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hedgedoc_whoamiA
Verify the current session is valid and return the logged-in user's profile. Returns JSON with user info (name, email, photo, provider, etc.). Call this to confirm the server is correctly authenticated before attempting write operations, or to identify which account is active.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the tool returns JSON with user fields, indicating it's a read-only informational call. It also implies verification behavior by saying 'verify session is valid,' which is sufficient for a tool of this simplicity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose and then provide usage context. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple: no parameters, no output schema. The description covers what it does, what it returns, and when to use it, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the input schema, so the baseline is 4. The description adds no param detail, and none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with specific verbs ('verify', 'return') and identifies the resource (current session, user profile). It distinguishes itself from sibling tools like hedgedoc_create_note and hedgedoc_read_note, which focus on notes, making it unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly advises calling this tool to confirm authentication before write operations or to identify the active account, providing a clear context of use. It doesn't explicitly name alternatives, but the write-operation mention effectively differentiates from note-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
6 tool updates
v0.1.0- First observed
hedgedoc_create_note - First observed
hedgedoc_list_history - First observed
hedgedoc_note_info - First observed
hedgedoc_read_note - First observed
hedgedoc_update_note - First observed
hedgedoc_whoami
TDQS
A4.4/5.0
Scored across 6 tools
Disambiguation5/5
Each tool performs a distinct function: create, read, update, metadata, session validation, and history. Even read_note and note_info are clearly separated by raw content vs. metadata.
Naming Consistency5/5
All tools use the 'hedgedoc_' prefix with clear verb_noun or noun_info naming in consistent snake_case. The pattern is uniform and predictable.
Tool Count5/5
Six tools is a well-scoped set for a HedgeDoc server, covering core note operations plus session and history. No unnecessary duplication or bloat.
Completeness4/5
Core lifecycle (create, read, update) is present, along with metadata and history. Missing delete is a notable gap, and update's alias-only limitation creates a dead end for non-alias notes, but the overall surface is reasonably complete.
Maintenance
ActivityMaintained
ResponsivenessNo issues
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