LogSeq▌
by dailydaniel
Integrate LogSeq for automated note-taking, knowledge graph analysis, and workflow automation. Boost productivity for de
Integrates with LogSeq API to enable automated note-taking, knowledge graph analysis, and workflow automation for developers and knowledge workers.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Knowledge workers automating note organization
- / Developers building LogSeq integrations
- / Researchers managing large knowledge bases
- / Teams standardizing documentation workflows
capabilities
- / Create and edit LogSeq pages programmatically
- / Insert and modify blocks within pages
- / Retrieve page details and content
- / Manage LogSeq knowledge graph structure
- / Automate note-taking workflows
- / Organize information with custom properties
what it does
Connects LLMs to your LogSeq knowledge base for automated note creation and organization. Allows programmatic interaction with LogSeq pages, blocks, and knowledge graphs.
about
LogSeq is a community-built MCP server published by dailydaniel that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate LogSeq for automated note-taking, knowledge graph analysis, and workflow automation. Boost productivity for de It is categorized under productivity.
how to install
You can install LogSeq in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
LogSeq is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Logseq MCP Server
A Model Context Protocol server that provides direct integration with Logseq's knowledge base. This server enables LLMs to interact with Logseq graphs, create pages, manage blocks, and organize information programmatically.
<a href="https://glama.ai/mcp/servers/@dailydaniel/logseq-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@dailydaniel/logseq-mcp/badge" alt="Logseq Server MCP server" /> </a>Usage with Claude Desktop
{
"mcpServers": {
"logseq": {
"command": "uvx",
"args": ["mcp-server-logseq"],
"env": {
"LOGSEQ_API_TOKEN": "<YOUR_KEY>",
"LOGSEQ_API_URL": "http://127.0.0.1:12315"
}
}
}
}
If you have errors, use 0.0.1 version:
{
"mcpServers": {
"logseq": {
"command": "uvx",
"args": ["mcp-server-logseq==0.0.1"],
"env": {
"LOGSEQ_API_TOKEN": "<YOUR_KEY>",
"LOGSEQ_API_URL": "http://127.0.0.1:12315"
}
}
}
}
Available Tools
Block Operations
-
logseq_insert_block - Create new blocks in Logseq Parameters:
parent_block(string): Parent block UUID or page namecontent(string, required): Block contentis_page_block(boolean): Create as page-level blockbefore(boolean): Insert before parent blockcustom_uuid(string): Custom UUIDv4 for block
-
logseq_edit_block - Enter block editing mode Parameters:
src_block(string, required): Block UUIDpos(number): Cursor position
-
logseq_exit_editing_mode - Exit editing mode Parameters:
select_block(boolean): Keep block selected
Page Operations
-
logseq_create_page - Create new pages Parameters:
page_name(string, required): Page nameproperties(object): Page propertiesjournal(boolean): Create as journal pageformat(string): Page format (markdown/org)
-
logseq_get_page - Get page details Parameters:
src_page(string, required): Page identifierinclude_children(boolean): Include child blocks
-
logseq_get_all_pages - List all pages Parameters:
repo(string): Repository name
Content Retrieval
-
logseq_get_current_page - Get active page/block Parameters: None
-
logseq_get_current_blocks_tree - Current page's block hierarchy Parameters: None
-
logseq_get_editing_block_content - Get content of active block Parameters: None
-
logseq_get_page_blocks_tree - Get page's block structure Parameters:
src_page(string, required): Page identifier
Prompts
logseq_insert_block
Create a new block in Logseq Arguments:
parent_block: Parent block reference (page name or UUID)content: Block contentis_page_block: Set true for page-level blocks
logseq_create_page
Create a new Logseq page Arguments:
page_name: Name of the pageproperties: Page properties as JSONjournal: Set true for journal pages
Installation
Using pip
pip install mcp-server-logseq
From source
git clone https://github.com/dailydaniel/logseq-mcp.git
cd logseq-mcp
cp .env.example .env
uv sync
Run the server:
python -m mcp_server_logseq
Configuration
API Key
- Generate API token in Logseq: API → Authorization tokens
- Set environment variable:
export LOGSEQ_API_TOKEN=your_token_here
Or pass via command line:
python -m mcp_server_logseq --api-key=your_token_here
Graph Configuration
Default URL: http://localhost:12315 To customize:
python -m mcp_server_logseq --url=http://your-logseq-instance:port
Examples
Create meeting notes page
Create new page "Team Meeting 2024-03-15" with properties:
- Tags: #meeting #engineering
- Participants: Alice, Bob, Charlie
- Status: pending
Add task block to existing page
Add task to [[Project Roadmap]]:
- [ ] Finalize API documentation
- Due: 2024-03-20
- Priority: high
Create journal entry with first block
Create journal entry for today with initial content:
- Morning standup completed
- Started work on new authentication system
Debugging
npx @modelcontextprotocol/inspector uv --directory . run mcp-server-logseq
Contributing
We welcome contributions to enhance Logseq integration:
- Add new API endpoints (page linking, query support)
- Improve block manipulation capabilities
- Add template support
- Enhance error handling
FAQ
- What is the LogSeq MCP server?
- LogSeq is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for LogSeq?
- This profile displays 38 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★38 reviews- ★★★★★Kwame Malhotra· Dec 24, 2024
Strong directory entry: LogSeq surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Anaya White· Dec 16, 2024
LogSeq is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Chaitanya Patil· Dec 4, 2024
LogSeq is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Nov 23, 2024
We evaluated LogSeq against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Noah Johnson· Nov 15, 2024
I recommend LogSeq for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Hassan Sanchez· Nov 7, 2024
According to our notes, LogSeq benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Isabella Jackson· Nov 7, 2024
Useful MCP listing: LogSeq is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Mia Park· Oct 26, 2024
We wired LogSeq into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Lucas Jackson· Oct 26, 2024
We evaluated LogSeq against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Shikha Mishra· Oct 14, 2024
Useful MCP listing: LogSeq is the kind of server we cite when onboarding engineers to host + tool permissions.
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