Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Extract text and metadata from local PDFs, and merge or split PDF files.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"pdfport": {
"command": "npx",
"args": [
"-y",
"@reneturcios/pdfport",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add pdfport -- npx -y @reneturcios/pdfport mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"pdfport": {
"command": "npx",
"args": [
"-y",
"@reneturcios/pdfport",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"pdfport": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/pdfport",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account CloudCorpRecords, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 7 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
pdfport does the five PDF jobs that come up over and over: pull the text out of a file, read its document metadata, summarise it (pages, page sizes, file size, PDF version), merge several files into one, and split a file into one document per page. It works on local files only — nothing is uploaded anywhere.
The engine is a small, genuine PDF implementation written in pure TypeScript for this project. No PDF library is bundled and there are no runtime dependencies beyond the MCP SDK. The engine scans a document's indirect objects, follows the Catalog to its Pages tree, decodes plain and FlateDecode content streams, and recovers text from the standard text-showing operators. Merges renumber the source objects into one new object graph with a rebuilt page tree; splits emit one document per page the same way; both write a freshly computed cross-reference table.
Supported: simple PDFs with a flat page tree (a Catalog whose Pages node lists Page objects directly — the shape common generators produce, and the shape pdfport's own merge/split write), uncompressed or FlateDecode streams, literal and hex strings in content and in the Info dictionary, and per-page MediaBox sizes (inherited from the Pages node when a page omits its own).
Not supported: encrypted files, object streams and compressed cross-reference streams (PDF 1.5+ compact files), nested page trees, embedded-font encodings that need a ToUnicode map to read, and form/annotation fidelity on merge or split. Files outside the subset fail with a plain error saying what was not found — pdfport never returns invented text or metadata.
npx @reneturcios/pdfport get-pdf-info ./report.pdf
Or run the container image:
docker run -i ghcr.io/cloudcorprecords/pdfport
The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.
# Print the document's text
pdfport extract-text ./report.pdf
pdfport get-metadata ./report.pdf
pdfport get-pdf-info ./report.pdf
pdfport merge ./combined.pdf ./a.pdf ./b.pdf ./c.pdf
pdfport split ./report.pdf ./report-pages
pdfport mcp
pdfport --version
Exit codes: 0 on success, 1 when a file is missing or a document cannot be processed (the error says which), 2 for usage errors.
One bin serves both faces. The mcp subcommand starts a stdio MCP server:
npx -y @reneturcios/pdfport mcp
MCP client configuration:
{
"mcpServers": { "pdfport": { "command": "npx", "args": ["-y", "@reneturcios/pdfport", "mcp"] } } }
| Tool | Input | What it returns |
|---|---|---|
extract_text | file_path (string, required) | The file's text: every page's shown text, pages joined with a newline. |
get_metadata | file_path (string, required) | The Info dictionary's title, author, subject, keywords, creator, producer and dates (only the fields the document carries), plus the page count. |
get_pdf_info | file_path (string, required) | Page count, each page's MediaBox size in points, the file size in bytes, and the PDF version from the header. |
merge_pdfs | input_files (array of strings, required), output_file (string, required) | Writes the merged document and reports the output path and total page count. The first input's metadata is kept. |
split_pdf | file_path (string, required), output_dir (string, required) | Writes one single-page file per page into the directory and reports the created file paths and page count. |
npm install
npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, no network npm run dev # run the CLI from source via tsx
The test suite builds small PDFs from raw strings — plain and FlateDecode content streams — and drives the default engine end-to-end: extraction (including TJ arrays and literal-string escapes), metadata, info, merge and split are all asserted against the real implementation, then the file facade is exercised against real files in a temporary directory.
MIT — see LICENSE.