This MCP server enables AI agents to read, search, and extract content from PDF files using specialized tools and SQLite-based caching for persistence across server restarts.
From the registry: Production-ready MCP server for PDF processing with intelligent caching.
Please install the `pdf-mcp` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Python 3.10+** — Python runtime required
Canonical MCP server config (stdio transport):
- command: `uvx`
- args: ["pdf-mcp"]
- optional environment variables:
- `PDF_MCP_CACHE_DIR`: Cache directory (default: ~/.cache/pdf-mcp) (example: `/path/to/cache`)
- `PDF_MCP_CACHE_TTL`: Cache TTL in hours (default: 24) (example: `24`)
Note: 8 tools for reading, searching, and extracting PDF content. Uses SQLite caching. Semantic search requires pip install 'pdf-mcp[semantic]' and downloads ~67MB ONNX model on first use.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.PDF_MCP_CACHE_DIRrequiredCache directory for storing cached PDF data.PDF_MCP_CACHE_TTLrequiredCache TTL in hours.Provide your AI coding tools with token-efficient access to up-to-date technical documentation for…