Pipeworx vs Glean
search the world's authoritative data vs search your company's knowledge
live answers from the world's public + proprietary data (877 sources) for AI agents over MCP.
enterprise search and AI assistants over your company's internal knowledge — docs, wikis, tickets, chats.
Glean indexes what your company knows — Drive, Slack, Jira, Confluence — and puts search and AI assistants on top, permission-aware. Pipeworx indexes nothing of yours: it's a gateway to what the WORLD knows, live — SEC filings, FDA records, economic series, patents, trials, markets — built for AI agents rather than employees. The boundary is the firewall: inside it, Glean's knowledge graph is the right tool; outside it, agents need authoritative, citable, current data, which is exactly the Pipeworx surface (including in-record semantic search via search_within, so an agent can find the relevant passage inside a 200-page filing the same way Glean finds the relevant doc inside your wiki).
Side-by-side
| Pipeworx | Glean | |
|---|---|---|
| Corpus | The world's authoritative sources — 877 live data packs | Your company's apps and documents, permission-aware |
| Primary consumer | AI agents over MCP | Employees (search UI, assistant) + agents; now also ships its own MCP Gateway for governing internal MCP servers |
| Semantic search | Across 3,690 tools (routing) AND inside fetched records (search_within: passage-level, offset-verified) | Across your indexed enterprise content |
| Freshness | Fetched live; _meta.fetched_at on every response | Connector sync cadence |
| Setup | One MCP URL, no signup for the first calls | Enterprise deployment with per-app connectors and permissions mapping |
When to use which
Use Glean if
- The answers live in your company's own documents, tickets, and chats
- You need permission-aware search that respects who can see what
- The consumer is your workforce, not an autonomous agent
Use Pipeworx if
- The answers live in public filings, statistics, registries, and markets
- Your consumer is an AI agent that needs structured, citable data over MCP
- You want passage-level search inside long public records (10-Ks, studies) without ingesting them anywhere
Connect Pipeworx in one line
Add this to your MCP client (Claude Desktop, Cursor, VS Code, Claude Code, etc.) — no API keys required for public data sources.
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}Common questions
Do Glean and Pipeworx overlap?
Barely — the firewall is the boundary. Glean is authoritative for what your organization knows; Pipeworx is authoritative for what the world publishes. Agents that need both connect to both: Glean (or its agent surface) for internal context, Pipeworx for external ground truth.
Is search_within a Glean replacement?
No — it's the same interaction pattern (semantic search that finds the relevant passage) applied to a single fetched public record, like a long SEC filing, with character offsets so the quote is verifiable. It doesn't index your documents and never sees your private data.
Glean ships an "MCP Gateway" too — same thing?
Same protocol, opposite direction. Glean's MCP Gateway (announced June 2026) governs your INTERNAL MCP servers — admin controls, permissions, prompt-injection checks — for tools inside the firewall. Pipeworx's gateway is the data itself: 877 curated live-data packs behind one URL, no servers of yours to govern. An enterprise could plausibly run both: Glean's gateway in front of internal tools, Pipeworx for the world's data.