Bear MCP Server
Shows integration with GitHub through CI/CD pipeline badges and repository hosting.
Integrates with the Bear Note Taking App on macOS, allowing for note creation, content retrieval, searching, and tag management through Claude Desktop.
Runs as a Node.js application to provide the MCP server functionality.
Distributes the MCP server as an npm package, as indicated by the npm version badge.
Uses Shields.io for status badges displaying CI/CD, license, and npm version information.
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., "@Bear MCP Serversearch my Bear notes for 'meeting notes' and show me the most recent one"
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.
Bear MCP Server
An MCP (Model Context Protocol) server for integrating Bear Note Taking App with Claude Desktop. This server allows Claude to read, create, and search your Bear notes directly.
✨ Features (v4.0.2)
Full data retrieval capabilities:
🔍 Search notes and get complete results with metadata
🏷️ Retrieve all tags from your Bear database
📖 Read note content for analysis and summarization
✏️ Create notes and get their IDs back
📝 Add text to existing notes
✅ Test setup with comprehensive status checking
Related MCP server: bear-notes-mcp
⚠️ Current Limitations & Usage Guidelines
Browser Window Behavior
Expected: Brief browser windows may appear during search/tags operations due to Bear's callback system.
Windows are automatically minimized and moved off-screen
Auto-close within 1-2 seconds in most cases
Safe to manually close if they persist
Focus is returned to your original window automatically
Search Reliability
Success Rate: ~80-90% of searches work reliably
Occasional timeouts may occur (20-second limit)
Simple terms work better than complex queries
Retry once if a search times out
Single words tend to be more reliable than phrases
Best Practices
✅ Recommended Usage:
Search my Bear notes for "project"
Get all my Bear tags
Create a note titled "Meeting Notes" with today's agenda
Add "Action item: Follow up" to my "Weekly Review" note⚠️ If Issues Occur:
Timeouts: Wait a moment and retry the same search
Browser windows: Safe to close manually if they don't auto-close
No results: Try simpler/broader search terms
Setup issues: Use
check_bear_setupto diagnose
Available Tools
Tool | Functionality | Reliability | Notes |
| Creates new notes | ✅ Excellent | Always works, returns ID |
| Adds text to notes | ✅ Excellent | Reliable text addition |
| Tests configuration | ✅ Excellent | Diagnostic tool |
| Searches notes | ⚠️ Good | ~80-90% success, may timeout |
| Lists all tags | ⚠️ Good | Usually works, brief popup |
| Retrieves note content | ⚠️ Good | Works well with valid IDs |
Installation
Clone the repository:
git clone https://github.com/philgetzen/bear-mcp.git
cd bear-mcpInstall dependencies:
npm installBuild the project:
npm run buildConfiguration in Claude Desktop
Add the server to your Claude Desktop configuration file:
macOS
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"bear": {
"command": "node",
"args": ["/path/to/bear-mcp/dist/index.js"]
}
}
}Windows
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"bear": {
"command": "node",
"args": ["C:\\path\\to\\bear-mcp\\dist\\index.js"]
}
}
}Bear Configuration
Required Settings:
Enable x-callback-url:
Open Bear → Settings (⌘,)
Go to "Advanced" tab
Enable "Allow x-callback-url"
Generate API Token (for search and tags):
Open Bear → Help → Advanced → API Token
Click "Copy Token"
In Claude, use:
set_bear_tokenwith your token
Usage Examples
Setup and Testing
Check my Bear setup and show me what's availableReliable Operations (Always Work)
Create a new Bear note titled "Project Ideas" with content about machine learning
Add "## Next Steps\n- Review documentation\n- Schedule follow-up" to my "Weekly Review" noteSearch Operations (Usually Work)
Search my Bear notes for "machine learning" and show me what you find
Get all my Bear tags and help me organize themContent Analysis (When Search Works)
Search for "meeting notes" then help me identify common action items across all results
Find notes tagged with "work" and summarize the main topicsTroubleshooting
"Search failed: Callback timeout"
Normal: Happens ~10-20% of the time
Solution: Wait 5-10 seconds and retry the same search
Tip: Try simpler search terms (single words work better)
"No token configured"
Get your token: Bear → Help → Advanced → API Token → Copy Token, then use set_bear_token
"Bear not found"
Make sure Bear is installed and has been opened at least once.
Browser windows appearing
Expected behavior due to Bear's callback system
Windows auto-minimize and move off-screen
Safe to manually close if they persist
Focus returns to your original window automatically
No search results
Check search term: Ensure it exists in your notes
Verify token: Use
check_bear_setupto testTry broader terms: Single words often work better than phrases
Check Bear directly: Verify the content exists in Bear app
Technical Details
HTTP Callback System
The server uses HTTP callbacks (port 51234) to receive data from Bear:
Bear sends search results and tag data via URL callbacks
Browser windows appear briefly due to this callback mechanism
20-second timeout for Bear responses
Auto-retry mechanisms for common failures
Performance Characteristics
Fast operations: Note creation, text addition (~1-2 seconds)
Medium operations: Single note retrieval (~3-5 seconds)
Slower operations: Search, tags list (~5-15 seconds)
Timeout threshold: 20 seconds maximum wait
Development
To run in development mode:
npm run devTo test the server:
npm run build
node dist/index.jsVersion History
v4.0.2: Enhanced browser window handling, 20s timeout
v4.0.1: Improved callback reliability, better error messages
v4.0.0: Full functionality restored with callback system
v3.1.0: Documentation-only version (limited functionality)
Requirements
Node.js 18 or higher
Bear app installed on your system
Claude Desktop application
macOS (Bear is macOS-only)
License
MIT
Available Tools
7 toolsadd_textB
Append or prepend text to an existing note
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Note unique identifier | |
| title | No | Note title (ignored if id is provided) | |
| text | Yes | Text to add | |
| mode | No | How to add the text (default: append) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose critical behavioral traits: whether this is a mutating operation (implied but not explicit), what happens if the note doesn't exist, whether changes are reversible, permission requirements, or rate limits. For a tool that modifies data without annotation coverage, this is insufficient.
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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for the tool's complexity. Every word earns its place.
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It should address behavioral aspects like error conditions (e.g., invalid note ID), what the operation returns, and whether it's idempotent. The current description provides only basic operational intent without necessary context for safe invocation.
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 100%, so the schema already documents all 4 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema (like explaining the 'mode' enum choices or interaction between 'id' and 'title'). Baseline 3 is appropriate when schema does the heavy lifting.
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 specific action ('append or prepend text') and target resource ('to an existing note'), distinguishing it from sibling tools like create_note (creates new notes) and get_note (reads notes). The verb+resource combination is precise and unambiguous.
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 implies usage by specifying 'to an existing note', suggesting it should not be used for creating new notes (use create_note instead). However, it lacks explicit guidance on when to choose append vs. prepend modes or alternatives like replace operations, and doesn't mention prerequisites like note existence verification.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_bear_setupB
Check if Bear is properly configured and test the connection
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks configuration and tests connection, implying a read-only diagnostic operation, but doesn't specify what 'properly configured' entails, what happens on success/failure (e.g., returns status vs. throws error), or any side effects (e.g., logging). This leaves gaps in understanding the tool's behavior.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core functionality ('Check if Bear is properly configured') and adds a clarifying detail ('and test the connection'). Every part of the sentence contributes value.
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 diagnostic nature (checking configuration and connection), the description is incomplete. No annotations exist to clarify safety or behavior, and there's no output schema to indicate what results are returned (e.g., success status, error details). The description should specify what constitutes a proper configuration or what the test entails to be fully helpful for 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 tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate as it doesn't miss any parameter-related information.
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 tool's purpose: 'Check if Bear is properly configured and test the connection.' It uses specific verbs ('check', 'test') and identifies the target resource (Bear setup/connection). However, it doesn't explicitly differentiate from sibling tools like 'set_bear_token' which might also involve configuration aspects.
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. It doesn't mention prerequisites (e.g., whether Bear must be installed first), nor does it suggest when to use it over sibling tools like 'set_bear_token' for configuration issues or 'search_notes' for connectivity testing through data retrieval.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_noteC
Create a new note in Bear and return its ID
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | Note title | |
| text | No | Note content | |
| tags | No | Comma separated tags (e.g., 'work,ideas') |
TDQS
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 mentions the tool creates a note and returns an ID, but omits critical details: whether this requires authentication, if there are rate limits, what happens on failure, or if the note is saved immediately. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
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 a single, efficient sentence that front-loads the core action ('Create a new note') and includes the key outcome ('return its ID'). There is no wasted verbiage, and every word earns its place by specifying the tool's purpose and result.
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 complexity of a creation tool with no annotations and no output schema, the description is incomplete. It fails to address behavioral aspects like authentication needs, error handling, or what the returned ID can be used for. The schema covers parameters well, but the overall context for safe and effective use is lacking.
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 100%, so the schema fully documents the three parameters (title, text, tags). The description adds no parameter-specific information beyond what the schema provides, such as examples or constraints. Baseline 3 is appropriate when the schema handles all parameter semantics.
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 ('Create a new note') and the resource ('in Bear'), with a specific outcome ('return its ID'). It distinguishes from siblings like 'add_text' or 'search_notes' by focusing on creation rather than modification or retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'set_bear_token' is unrelated).
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 'add_text' (which might append to existing notes) or 'search_notes' (for finding notes). It lacks context about prerequisites (e.g., authentication via 'set_bear_token') or typical use cases, leaving the agent to 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.
get_noteC
Get the content of a specific note
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Note unique identifier | |
| title | No | Note title (used if id is not provided) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits like whether this is a read-only operation, what happens if the note doesn't exist, authentication needs, rate limits, or return format. The description is minimal and lacks critical context for safe invocation.
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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loads the core purpose immediately.
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 simplicity (2 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what 'content' includes (e.g., text, metadata), error conditions, or how to handle the id/title parameters effectively. For a retrieval tool with no annotations, more context is needed for reliable use.
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 100%, so the schema already documents both parameters ('id' and 'title') with their descriptions. The description adds no additional meaning about parameters beyond implying retrieval of a 'specific note', which aligns with the schema but doesn't provide extra syntax, format details, or usage examples.
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') and resource ('content of a specific note'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'search_notes' or 'get_tags', but it's not misleading or tautological.
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 'search_notes' or 'create_note'. It mentions retrieving a 'specific note' but doesn't clarify if this requires knowing the exact ID/title versus searching. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tagsB
Get all tags from Bear (requires token)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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. It mentions authentication requirement ('requires token') which is valuable, but doesn't describe what 'Get all tags' actually means operationally - whether this returns all tags in the system, tags for current user, pagination behavior, or format of returned data. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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 - just 6 words total. It's front-loaded with the core purpose ('Get all tags from Bear') followed by the crucial prerequisite information ('requires token'). Every word earns its place with no redundancy or wasted space.
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 no annotations, no output schema, and a tool that presumably returns data (tags), the description is incomplete. It doesn't explain what format the tags come in, whether this is a read-only operation, what scope of tags are returned, or any error conditions. For a data retrieval tool with zero structured metadata, the description should provide more operational 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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't waste space discussing non-existent parameters, earning a baseline score of 4 for zero-parameter tools.
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 all tags') and resource ('from Bear'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'search_notes' or 'get_note', but the verb+resource combination is specific enough for basic understanding.
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 mentions 'requires token' which provides some context about prerequisites, but offers no guidance on when to use this tool versus alternatives like 'search_notes' or how it relates to other tag-related operations. There's no explicit when/when-not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_notesC
Search for notes and return results with metadata (requires token)
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | Search term | |
| tag | No | Tag to search within |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds 'requires token', indicating an authentication need, which is useful context beyond the input schema. However, it lacks details on other behavioral traits, such as whether the search is case-sensitive, how results are paginated or sorted, what metadata is included, or any rate limits. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 concise and front-loaded, stating the core purpose in a single sentence: 'Search for notes and return results with metadata'. The additional note '(requires token)' is brief and relevant. There's no wasted text, making it efficient, though it could be slightly more structured by separating usage notes into a distinct part.
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 complexity of a search operation with no annotations and no output schema, the description is incomplete. It mentions authentication but omits critical details like the format of returned metadata, error handling, or search scope. For a tool that returns results, the lack of output schema means the description should compensate by explaining return values, which it doesn't do, leaving the agent with insufficient context to use the tool effectively.
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 description coverage is 100%, with clear descriptions for both parameters ('term' and 'tag'), so the schema does the heavy lifting. The description doesn't add any meaning beyond what the schema provides, such as explaining how the parameters interact (e.g., if 'tag' narrows the search) or providing examples. This meets the baseline of 3, as the schema adequately documents the parameters without extra value from the description.
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 tool's purpose: 'Search for notes and return results with metadata'. It specifies the verb ('search'), resource ('notes'), and output ('results with metadata'), which is specific and actionable. However, it doesn't differentiate this search tool from potential alternatives among its siblings, such as 'get_note' or 'get_tags', which might also retrieve note-related data.
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 minimal guidance: it mentions 'requires token', which hints at an authentication prerequisite but doesn't specify when to use this tool versus alternatives like 'get_note' (which fetches a single note) or 'get_tags' (which retrieves tags). There's no explicit advice on when to use it, when not to, or what makes it distinct from sibling tools, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_bear_tokenB
Set the Bear app token for accessing existing notes. Get your token from Bear → Help → Advanced → API Token
| Name | Required | Description | Default |
|---|---|---|---|
| token | Yes | Your Bear app token |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the action ('Set the Bear app token') and provides token acquisition instructions, but it doesn't disclose key behavioral traits such as whether this is a one-time setup, if it persists across sessions, what happens on invalid tokens, or any rate limits. For a configuration tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 concise and well-structured in two sentences: the first states the purpose, and the second provides actionable instructions. Every sentence earns its place by delivering essential information without redundancy, making it efficient and front-loaded for quick understanding.
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 (a simple configuration tool with one parameter) and the absence of annotations and output schema, the description is moderately complete. It covers the basic purpose and token acquisition, but it lacks details on behavioral aspects like persistence, error handling, or integration with sibling tools. For a setup tool, this is adequate but leaves room for improvement in guiding the agent on usage 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 input schema has 100% description coverage, with the parameter 'token' documented as 'Your Bear app token.' The description adds minimal value beyond the schema by reinforcing the token's purpose ('for accessing existing notes') and providing acquisition instructions, but it doesn't add syntax or format details. With high schema coverage, the baseline score of 3 is appropriate as the description offers slight contextual enhancement.
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 tool's purpose with a specific verb ('Set') and resource ('Bear app token'), and it explains the token is for 'accessing existing notes.' However, it doesn't explicitly differentiate this from sibling tools like 'check_bear_setup' or explain why setting a token is separate from other 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 implies when to use this tool by stating it's for 'accessing existing notes' and providing instructions on how to obtain the token, but it doesn't explicitly state when to use it versus alternatives (e.g., before calling other tools like 'get_note' or 'search_notes') or mention any prerequisites. The guidance is practical but lacks explicit context about timing or exclusions.
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. Dates show when Glama detected each change.
7 tool updates
- First observed
add_text - First observed
check_bear_setup - First observed
create_note - First observed
get_note - First observed
get_tags - First observed
search_notes - First observed
set_bear_token
TDQS
Each tool has a clearly distinct purpose with no overlap: add_text modifies note content, check_bear_setup handles configuration, create_note and get_note manage note lifecycle, get_tags retrieves metadata, search_notes finds notes, and set_bear_token handles authentication. The descriptions make it easy to distinguish between them.
All tools follow a consistent verb_noun pattern using snake_case: add_text, check_bear_setup, create_note, get_note, get_tags, search_notes, set_bear_token. The naming is predictable and readable throughout the set.
With 7 tools, this is well-scoped for a Bear note-taking server. It covers core operations (create, read, update via add_text, search) and necessary setup/authentication without being overwhelming or too sparse.
The toolset provides strong coverage for note management: create, read, update (via add_text), search, and tag retrieval. Minor gaps include no explicit delete_note or update_note (beyond add_text), but agents can work around this, and the surface supports core workflows effectively.
Maintenance
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