DocPull runs on your own machine — the client starts it, so there is no endpoint to ping. 1 920 installs a week from pypi. Last commit 5 Sep 2026.
Sync public web sources into cited context packs for AI agents, RAG, and MCP clients.
What the code does
We read the source, 20 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
start += MAX_EMBEDDING_ROWS_PER_INSERT
) {
const slice = docs.slice(start, start + MAX_EMBEDDING_ROWS_PER_INSERT);
const child = spawn(command, [...args], {
completed = subprocess.run( # nosec B603, B607
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
This code can reach further than it looks
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
Connect this server
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add docpull -- uvx docpull{
"mcpServers": {
"docpull": {
"args": [
"docpull"
],
"command": "uvx"
}
}
}[mcp_servers.docpull]
command = "uvx"
args = ["docpull"]{
"mcpServers": {
"docpull": {
"args": [
"docpull"
],
"command": "uvx"
}
}
}{
"mcpServers": {
"docpull": {
"args": [
"docpull"
],
"command": "uvx"
}
}
}Alternatives to DocPull
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Extract PDFs to Markdown, RAG chunks and cited tables; publish tracked Doc Links with read stats.
Protected RAG storage — agents discover public metadata, content only by access token.
RAG-enabled MCP server using Contextual AI. Supports single-agent and multi-agent modes.
Ingest, manage, and retrieve documents for RAG-powered AI applications
DocPull — questions
Answers built from our own checks of this server.