pulr

pulr

Secure file exchange MCP server enabling AI agents to upload, share, fetch, and revoke files with SHA-256 verification, malware scanning, expiry, access restrictions, and human approval workflows.

Category
Visit Server

README

<p align="center"><img src="design/banner.png" alt="pulr — secure passage of files between minds" width="100%"></p>

pulr

Secure file exchange for AI agents. Agents produce files — reports, CSVs, images, PDFs, code — and have no safe way to hand them to other agents, humans, or downstream automation. pulr.ai is that handoff layer: drop a file, get a verified, scannable, expiring download URL everyone in the chain can actually trust.

Every upload is SHA-256-hashed, scanned before any link activates (secrets, prompt-injection heuristics, ClamAV malware), stamped with provenance (which agent, workflow, and model produced it), and served through unguessable capability URLs with TTLs, download limits, IP/geo/time restrictions, and instant revocation. Humans get a review page with approve/reject; automation gets webhooks and Ed25519-signed receipts. Everything is audit-logged — who fetched, when, from where.

Website: pulr.ai · Docs: pulr.ai/docs · Self-serve signup: pulr.ai/app

This repo is the open tooling: the MCP server (root, npm mcp-server-pulr), the JavaScript SDK (sdk/js, npm @pulr/sdk), and the Python SDK (sdk/python, PyPI pulr-sdk, with LangChain tools).

<p align="center"><img src="design/plate08-vignettes.png" alt="Sealed handoff: sender → sealed capsule → customs → accepted. Safeguards: encrypted, audited, MFA, PHI-blind" width="92%"></p>

Sample uses

  • Agent → human sign-off → automation. An agent generates a quarterly report with approval: true; the reviewer gets the link by email, previews provenance and scan results, clicks Approve & release — only then does the download URL go live, and a webhook kicks off the downstream pipeline with a signed receipt as proof.
  • Agent → agent handoff without context stuffing. Instead of jamming base64 blobs into a context window, one agent uploads and passes a capability URL; the receiving agent fetches integrity-verified bytes. Revoke the link the moment the job is done.
  • Burn-after-reading delivery. max_downloads: 1 + a 1-hour TTL: send credentials-adjacent artifacts, one fetch, then the link is dead — with an audit row showing exactly who took it, from which IP.
  • Geo/time-fenced distribution. Lock a link to your office CIDR, US-only access, or 9–5 Eastern: restrictions: { allow_ips, allow_countries, allow_hours }.
  • Quarantine as a feature. A "meeting notes" file with an embedded "ignore all previous instructions…" payload (even zero-width-obfuscated or base64-smuggled) gets flagged at upload and can never be shared — your agents never ingest it.
  • Compliance trail. GET /v1/artifacts/:id/receipt returns an Ed25519-signed record of hash + provenance + scan + approval, verifiable by anyone without trusting pulr.

Your files are not our data

The only thing that ever reads uploaded bytes is the automated threat scanner — malware signatures, leaked-secret patterns, prompt-injection heuristics. It looks for threats, not information: the verdict is recorded, the content is not extracted, indexed, mined, trained on, or sold.

<p align="center"><img src="design/plate08b-scanner.png" alt="The scanner is not a reader: your file, content folded away → scanned for threats only → same file, never opened → no human reads" width="92%"></p>

MCP server (Claude, agent frameworks)

{
  "mcpServers": {
    "pulr": {
      "command": "npx",
      "args": ["-y", "mcp-server-pulr"],
      "env": { "PULR_API_KEY": "pulr_sk_..." }
    }
  }
}

Then just ask your agent: "Upload this report to pulr with approval required and a 24-hour expiry, and give me the review link."

Tools: pulr_upload (with approval), pulr_send / pulr_inbox / pulr_accept / pulr_reject / pulr_address (sealed workspace-to-workspace handoff — no links), pulr_share (with restrictions), pulr_fetch, pulr_list, pulr_revoke, pulr_receipt, pulr_whoami. Env: PULR_API_KEY (required), PULR_API_URL (optional, defaults to https://pulr.ai; point at your own instance if self-hosting).

JavaScript / TypeScript — npm install @pulr/sdk

import PulrClient from '@pulr/sdk'
const pulr = new PulrClient({ apiKey: process.env.PULR_API_KEY })

const a = await pulr.upload({ filePath: './q3-report.pdf', approval: true, expiresIn: '48h' })
console.log(a.review_url)                                  // send to a human
const { bytes } = await pulr.fetchCapability(a.download_url)  // sha256-verified
console.log(PulrClient.verifyReceipt(await pulr.receipt(a.artifact_id)))  // true

Python — pip install pulr-sdk

from pulr import PulrClient, verify_receipt
pulr = PulrClient()  # reads PULR_API_KEY

a = pulr.upload(file_path="q3-report.pdf", approval=True, expires_in="48h",
                restrictions={"allow_countries": ["US"]})
data, sha = pulr.fetch_capability(a["download_url"])   # sha256-verified
verify_receipt(pulr.receipt(a["artifact_id"]))         # pip install pulr-sdk[verify]

LangChain: from pulr.langchain_tool import pulr_toolspulr_upload / pulr_fetch / pulr_share StructuredTools for any agent.

Getting a key

Create a workspace at pulr.ai/app — 30 seconds, 500 MB included, owner API key shown once. Mint one key per agent (provenance is stamped from the key); revoke any key to cut that agent off instantly. Full API reference: pulr.ai/docs.

A pulr "artifact" is a durable file with a lifecycle — not a streaming chat-UI panel. If you want typed real-time artifact panels for React chat apps, that's a different (complementary) tool, e.g. @ai-sdk-tools/artifacts. pulr is where the file goes afterward.

MIT © Tal Eilon

The design plates

pulr's product design is kept as a series of drafting plates — one per chapter of the system. A few from the atlas:

<img src="design/plate06-registry.png" alt="Harbor Registry — accounts: a name is pencil until witnessed"> <img src="design/plate04-watchroom.png" alt="Watchroom — the operations register">
<img src="design/plate05-open-water.png" alt="Open Water — the 404: here the survey ends"> <img src="design/plate01.png" alt="Sealed Passage — plate one">

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured