Logseq知识库交互服务

claude mcp add logseq \
  -e LOGSEQ_DIR="~/logseq-graph" \
  -e CACHE_TTL=300 \
  -- poetry run python /path/to/mcp-python-logseq/server.py

poetry run fastmcp install claude-code server.py \
  --server-name "logseq" \
  --env LOGSEQ_DIR=~/logseq-graph \
  --env CACHE_TTL=300

{
  "mcpServers": {
    "logseq": {
      "command": "poetry",
      "args": [
        "run",
        "python",
        "/path/to/mcp-python-logseq/server.py"
      ],
      "env": {
        "LOGSEQ_DIR": "~/logseq-graph",
        "CACHE_TTL": "300"
      }
    }
  }
}

"Search my notes for 'machine learning'"

"Show me my notes on the Python project"

"What notes do I have tagged with #work?"

"Show me journal entries from last week"

"Summarize all my notes for the website redesign project"

.
├── server.py              # Main MCP server implementation
├── pyproject.toml         # Poetry configuration
├── README.md             # This file
├── doc.md                # Installation guide
├── fastmcp_documentation.md  # FastMCP reference
└── command.txt           # Example CLI commands

# Set environment variables
export LOGSEQ_DIR="~/Documents/MyLogseqGraph"
export CACHE_TTL=300

# Run the server
poetry run python server.py

npx @modelcontextprotocol/inspector poetry run python server.py