ContextBolt Bookmarks
Officialcontextbolt-mcp
MCP server for ContextBolt. Lets Claude Desktop and Claude Code search and save your bookmarks.
Pro plan required. Get your token from the ContextBolt extension under Settings → Pro Features.
Looking for other servers to pair with this one? Browse the MCP server directory.
Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"contextbolt": {
"command": "npx",
"args": ["-y", "contextbolt-mcp"],
"env": {
"CONTEXTBOLT_TOKEN": "your_token_here"
}
}
}
}Restart Claude Desktop. The bookmarks tools appear automatically.
Related MCP server: MyAITwin MCP
Claude Code
Add to .mcp.json in any project, or ~/.claude/mcp.json for global use. The URL form is simpler than the stdio form here:
{
"mcpServers": {
"contextbolt": {
"url": "https://api.contextbolt.app/mcp/your_token_here"
}
}
}Tools
search_bookmarks(query, limit?, platform?): semantic search across your saved contentlist_clusters(): your topic clusters with bookmark countsget_cluster_bookmarks(cluster_id, limit?): all bookmarks in one clusterget_recent_bookmarks(limit?, platform?): most recently saved bookmarkssave_bookmark(url, content, title?, author?, tags?): create a new bookmark while chatting
The server lists its tools without a token, so clients and registries can discover them. A Pro token (CONTEXTBOLT_TOKEN) is only required to actually call a tool.
Troubleshooting
If Claude Desktop says the server failed to start, check:
CONTEXTBOLT_TOKENis set in theenvblockYour ContextBolt account is on the Pro plan
Node 18+ is installed (
node --version)
For support: https://contextbolt.com/support/
Available Tools
5 toolsget_cluster_bookmarksB
Get all bookmarks in one topic cluster.
| Name | Required | Description | Default |
|---|---|---|---|
| cluster_id | Yes | Cluster identifier from list_clusters. | |
| limit | No | Maximum bookmarks to return. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description says 'all bookmarks' but the schema includes a 'limit' parameter that caps the number, creating a contradiction. No behavioral traits like pagination, ordering, or required permissions are disclosed.
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 sentence with no waste, but it is too terse and omits necessary context. Still efficient for its length.
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?
The description does not explain what a topic cluster is, does not describe the return format, and conflicts with the limit param. Given no output schema, it is inadequate.
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 baseline is 3. The description adds no extra meaning beyond what the schema provides for cluster_id and limit.
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 verb 'Get' and the resource 'all bookmarks in one topic cluster', which distinguishes it from siblings like get_recent_bookmarks (recent) and search_bookmarks (search).
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?
No guidance is provided on when to use this tool vs alternatives such as get_recent_bookmarks or search_bookmarks. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_recent_bookmarksB
Get your most recently saved bookmarks.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum bookmarks to return (default 10). | |
| platform | No | Optional source filter. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description does not disclose behavioral traits such as sorting order, timeframe for 'recent,' or whether the tool supports pagination. The description adds minimal behavioral context 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 with one sentence and five words, no fluff. However, it could be slightly expanded to include key behavioral details without becoming verbose.
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 output schema and a simple tool, the description should explain what the tool returns, but it only says 'recently saved bookmarks' without specifying return format, ordering, or what 'recent' means.
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%, and the tool description does not add any extra meaning beyond what the schema already provides. With full schema coverage, baseline is 3.
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 verb 'Get' and the resource 'your most recently saved bookmarks,' distinguishing it from siblings like get_cluster_bookmarks and search_bookmarks.
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?
No guidance on when to use this tool versus alternatives like search_bookmarks or get_cluster_bookmarks. The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_clustersB
List your topic clusters with their bookmark counts.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, pagination, ordering, or authentication requirements. For a list operation, it only states output but not any constraints or side effects.
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, clear sentence that front-loads the purpose: 'List your topic clusters with their bookmark counts.' No unnecessary words.
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 simplicity of the tool (no parameters, no output schema, no annotations), the description is minimal. It does not explain what a topic cluster is, nor does it mention ordering, filtering, or that the list is limited to the user's clusters. The context from sibling tools is not leveraged.
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 no parameters, and schema description coverage is 100%. With zero parameters, the description does not need to add parameter meaning; the baseline score of 4 is appropriate.
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 uses the specific verb 'List' and resource 'topic clusters' with 'their bookmark counts', which clearly states what the tool does and distinguishes it from sibling tools like get_cluster_bookmarks (which gets bookmarks for a specific cluster) and search_bookmarks (which searches bookmarks).
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 does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites, scope, or typical use cases. It only says 'your topic clusters', implying personal scope but lacks explicit directives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_bookmarkB
Save a new bookmark to your ContextBolt collection while chatting.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the page or post to save. | |
| content | Yes | Main text content to index. | |
| title | No | Optional title. | |
| author | No | Optional author or handle. | |
| tags | No | Optional tags. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It only says 'save a new bookmark', but does not disclose potential side effects (e.g., duplication, required authentication) or behavior details.
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?
Single, front-loaded sentence with no wasted words.
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 5 parameters (2 required) and no output schema, the description is too sparse. It does not explain return format, error handling, or post-save behavior, which would help an agent anticipate outcomes.
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 baseline is 3. The description adds no extra meaning beyond the parameter descriptions already in the 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 verb 'save' and resource 'bookmark', and distinguishes itself from siblings like search_bookmarks or get_recent_bookmarks by specifying the context 'while chatting'.
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?
No guidance on when to use this tool versus alternatives (e.g., search_bookmarks). Does not mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_bookmarksA
Semantic search across your saved bookmarks from X, Reddit, LinkedIn, and the web.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural-language search query. | |
| limit | No | Maximum results to return (default 10). | |
| platform | No | Optional source filter, e.g. 'twitter', 'reddit', 'linkedin', 'web'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It describes the tool as performing 'semantic search,' which is clear but lacks details on whether it is read-only, expensive, or what the response format is, leaving moderate 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 a single clear sentence that is front-loaded and contains no unnecessary words.
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?
The tool lacks an output schema, but the description does not explain what the search returns (e.g., a list of bookmarks with metadata). Given the simplicity of the tool, this is a notable omission, especially for an AI 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?
Schema coverage is 100%, so the schema already describes all parameters. The description does not add additional meaning beyond the schema, so baseline 3 is appropriate.
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 'Semantic search across your saved bookmarks' with a specific verb and resource, and distinguishes from sibling tools like get_recent_bookmarks and get_cluster_bookmarks by emphasizing semantic search and platform sources.
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 for searching bookmarks semantically but does not provide explicit guidance on when to use versus alternatives like get_recent_bookmarks or get_cluster_bookmarks, nor does it mention 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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
5 tool updates
- First observed
get_cluster_bookmarks - First observed
get_recent_bookmarks - First observed
list_clusters - First observed
save_bookmark - First observed
search_bookmarks
TDQS
Each tool targets a distinct operation: cluster retrieval, recent list, cluster listing, saving, and search. No overlap in purpose.
All tool names follow a consistent verb_noun pattern with underscores (e.g., get_cluster_bookmarks, save_bookmark). No style mixing.
Five tools cover the essential bookmark operations (create, retrieve by cluster/recent/search, list clusters). Slightly thin but well-scoped for a focused server.
Missing update and delete operations for bookmarks, and no get-by-id tool. Basic retrieval and creation present, but lifecycle incomplete.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
AI research library. Save, organise and reuse notes and webpages as clean markdown context.
Search everything you save: YouTube, articles, podcasts, PDFs, Notion, Obsidian. API key or OAuth.
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Persistent context for Claude. Your AI always knows your projects and next actions across sessions.
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