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Turn any PDF folder into a searchable MCP server

Project description

pdf2mcp

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PyPI License: MIT Python 3.10+

Turn any PDF folder into a searchable MCP server with semantic search.

Installation

From PyPI (recommended)

pip install pdf2mcp

Or with uv:

uv tool install pdf2mcp

From source

git clone https://github.com/iSamBa/pdf2mcp.git
uv tool install ./pdf2mcp

To update after pulling new changes:

uv tool install --force ./pdf2mcp

Verify

pdf2mcp --version

Quick Start

# 1. Scaffold a project (creates docs/ and .env)
pdf2mcp init ./my-project
cd my-project

# 2. Add your PDFs to docs/ and set OPENAI_API_KEY in .env

# 3. Ingest
pdf2mcp ingest

# 4. Start the server
pdf2mcp serve

# 5. Get config snippets for your MCP client
pdf2mcp config

Architecture

pdf2mcp separates server and client concerns:

  • Server (pdf2mcp serve) — runs independently, handles PDF ingestion, embedding, and search. Configured via PDF2MCP_* environment variables.
  • Client (Claude Code, Cursor, VS Code, etc.) — connects to a running server over HTTP. Only needs the server URL.

The default transport is streamable-http. The server listens on http://127.0.0.1:8000/mcp and shuts down gracefully on SIGINT/SIGTERM.

Commands

Command Description
pdf2mcp init [dir] Scaffold a working directory with docs/ and .env
pdf2mcp ingest Parse PDFs, chunk, embed, and store in vector DB
pdf2mcp serve Start the MCP server (HTTP by default)
pdf2mcp config Print ready-to-paste config for MCP clients

Common Flags

# Override docs directory
pdf2mcp ingest --docs-dir ./my-pdfs
pdf2mcp serve --docs-dir ./my-pdfs

# Use stdio transport (for clients that spawn the server)
pdf2mcp serve --transport stdio

# Custom host/port
pdf2mcp serve --host 0.0.0.0 --port 9000

# Custom server name
pdf2mcp serve --name my-docs

# Config for a specific client
pdf2mcp config --client cursor
pdf2mcp config --client claude-desktop --transport stdio

Client Configuration

pdf2mcp config generates ready-to-paste JSON for all supported clients. The default is HTTP — clients just need the server URL:

{
  "mcpServers": {
    "pdf-docs": {
      "type": "http",
      "url": "http://127.0.0.1:8000/mcp"
    }
  }
}
Client Config File Top-level Key HTTP Support
Claude Code .mcp.json mcpServers Yes
Claude Desktop claude_desktop_config.json mcpServers No (stdio only)
Cursor .cursor/mcp.json mcpServers Yes
VS Code / Copilot .vscode/mcp.json servers Yes

Use --transport stdio for clients that need to spawn the server process (e.g., Claude Desktop):

{
  "mcpServers": {
    "pdf-docs": {
      "command": "uv",
      "args": ["run", "pdf2mcp", "serve"]
    }
  }
}

Environment Variables

Server settings (PDF2MCP_*)

These configure the server process. MCP clients never need these.

Variable Default Description
OPENAI_API_KEY (required) OpenAI API key for embeddings
PDF2MCP_OPENAI_BASE_URL https://api.openai.com/v1 OpenAI API base URL (for Azure, local proxies, or compatible providers)
PDF2MCP_DOCS_DIR docs Directory containing PDF files
PDF2MCP_DATA_DIR data Directory for vector database
PDF2MCP_EMBEDDING_MODEL text-embedding-3-small OpenAI embedding model
PDF2MCP_CHUNK_SIZE 500 Target chunk size in tokens
PDF2MCP_CHUNK_OVERLAP 50 Overlap between chunks in tokens
PDF2MCP_DEFAULT_NUM_RESULTS 5 Default search results count
PDF2MCP_SERVER_NAME pdf-docs MCP server name
PDF2MCP_SERVER_TRANSPORT streamable-http Transport protocol
PDF2MCP_SERVER_HOST 127.0.0.1 Host to bind to
PDF2MCP_SERVER_PORT 8000 Port to bind to

Client settings (PDF2MCP_CLIENT_*)

These configure how a client connects to the server. No secrets needed.

Variable Default Description
PDF2MCP_CLIENT_SERVER_NAME pdf-docs Server name in client config
PDF2MCP_CLIENT_SERVER_URL http://127.0.0.1:8000/mcp Server URL
PDF2MCP_CLIENT_TRANSPORT streamable-http Transport protocol

MCP Tools

The server exposes six tools:

Tool Description
search_docs(query) Semantic search across all ingested PDFs
search_in_doc(query, filename) Semantic search scoped to a single document
list_docs() List all ingested documents with chunk counts
get_sections(filename) Get section headings for a specific document
read_page(filename, page) Read the full content of a specific page
read_section(filename, section_title) Read the full content of a named section

Typical workflow

  1. list_docs — discover available documents
  2. get_sections — browse a document's structure
  3. read_section or read_page — read specific content
  4. search_docs or search_in_doc — find information by query

Development

git clone https://github.com/iSamBa/pdf2mcp.git
cd pdf2mcp
uv sync --all-extras
uv run pytest
uv run ruff check src/
uv run mypy src/

License

MIT

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