Used for loading environment variables to configure the MCP server with authentication credentials and API endpoints for the Yonote service.
Provides API tools to interact with Yonote documents and collections, which is described as an alternative to Notion. Allows listing documents/collections, retrieving document details, and navigating the content hierarchy.
Click on "Install 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., "@Yonote MCP Server list my recent documents"
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.
This is an MVP project of an MCP server for the Yonote service, an alternative to Notion. The server provides API tools to interact with Yonote documents and collections.
List documents and collections from Yonote
Get detailed information about a document
Exposes tools via the FastMCP framework
Related MCP server: SiYuan MCP Server
Python 3.13+
The following Python packages (see pyproject.toml):
fast-agent-mcp>=0.2.23
requests>=2.32.3
python-dotenv (for loading environment variables)
uv for dependency management
To install Yonote Document Interaction Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @cutalion/yonote-mcp --client claudeClone the repository:
git clone <your-repo-url>
cd yonote-mcpInstall dependencies using uv:
uv pip install -r requirements.txt
# or, using pyproject.toml:
uv pip install .Configure environment variables:
Create a .env file in the project root with the following content:
API_TOKEN=your_yonote_api_token
API_BASE_URL=https://app.yonote.ru/api # Optional, defaults to this valueRun the MCP server:
python main.pyThe server exposes the following tools:
documents_list: Get a list of documents (with optional limit, offset, and collectionId)
documents_info: Get info about a document by ID
collections_list: Get a list of collections (with optional limit and offset)
main.py — Main server code and tool definitions
pyproject.toml — Project metadata and dependencies
MIT (or specify your license)
To use this MCP server with Cursor, add the following to your ~/.cursor/mcp.json configuration file:
{
"mcpServers": {
"yonote": {
"command": "uv",
"args": [
"run",
"-v",
"--directory",
"/path/to/yonote-mcp",
"/path/to/yonote-mcp/main.py"
]
}
}
}Replace /path/to/yonote-mcp with the actual path to your project directory.
Get list of collections
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Get list' implies a read operation, but it doesn't disclose behavioral traits like whether it's paginated, requires authentication, has rate limits, or what happens with the limit/offset parameters. The description adds minimal value beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence, 'Get list of collections', which is front-loaded and wastes no words. It efficiently states the core action without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return format, pagination behavior, or parameter usage, making it inadequate for an agent to use the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions no parameters, failing to explain the meaning or usage of 'limit' and 'offset' (e.g., pagination details). This leaves significant gaps in understanding how to invoke the tool effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get list of collections' states the basic purpose (verb+resource) but is vague about scope and differentiation. It doesn't specify whether this returns all collections, user collections, or some subset, nor does it distinguish from sibling tools like 'documents_list' which might handle similar listing operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, context for usage, or comparison with sibling tools like 'documents_list' or 'documents_info', leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get info about a document by id
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get info' implies a read-only operation, it doesn't specify whether authentication is required, rate limits apply, what information is returned, or how errors are handled. This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise at just 6 words, front-loading the essential information with zero wasted words. Every element ('Get info', 'about a document', 'by id') earns its place in this minimal formulation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, 0% schema description coverage, and no output schema, the description is insufficiently complete. A read operation tool needs more context about what information is returned, error handling, and usage constraints to be fully usable by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It mentions 'by id' which clarifies the purpose of the single parameter, but doesn't explain what format the ID should be (numeric, UUID, etc.), where to obtain it, or validation rules. This provides minimal value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get info') and target resource ('about a document by id'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'documents_list' (which presumably lists multiple documents rather than retrieving a single one), preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'documents_list' or 'collections_list'. It doesn't specify prerequisites, error conditions, or typical use cases, leaving the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get list of documents
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| offset | No | ||
| collectionId | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Get list' implies a read operation, but it doesn't disclose important traits like whether this requires authentication, has rate limits, returns paginated results, or what happens with the parameters. The description adds minimal value beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words. It's front-loaded with the core purpose and contains zero wasted words. While under-specified, it's structurally efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, how parameters work, or behavioral characteristics. The agent would struggle to use this tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate but doesn't mention any parameters. Three parameters (limit, offset, collectionId) are completely undocumented in both schema and description. The description provides no information about what these parameters do or how they affect the document listing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get list of documents' clearly states the verb ('Get') and resource ('documents'), but it's vague about scope and doesn't differentiate from sibling tools like 'collections_list' or 'documents_info'. It doesn't specify whether this lists all documents, recent documents, or documents with particular characteristics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'collections_list' or 'documents_info'. There's no mention of prerequisites, appropriate contexts, or exclusions. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
collections_listdocuments_infodocuments_listEach tool has a clearly distinct purpose: collections_list retrieves collections, documents_info gets details of a specific document, and documents_list lists documents. There is no overlap in functionality, making it easy for an agent to select the right tool without confusion.
All tool names follow a consistent verb_noun pattern with snake_case: collections_list, documents_info, and documents_list. The naming is predictable and readable throughout, with no deviations or mixed conventions.
With only 3 tools, the server feels thin for a note-taking domain, as it lacks essential operations like creating, updating, or deleting collections or documents. While the tools are well-scoped individually, the count is borderline low for covering basic CRUD workflows.
The tool surface is significantly incomplete for a note-taking server. It only provides read operations (list and get info) for collections and documents, with no ability to create, update, or delete resources. This will likely cause agent failures when trying to perform common tasks like adding or modifying notes.
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