FRENES

Memory and knowledge · MCP server

PipesHub: MCP server, setup and security

PipesHub is an open-source MCP server that lets an AI agent search enterprise applications with permission-aware retrieval and RAG capabilities. Its repository has 17 stars and its last commit is from October 24, 2026 and it is licensed under Apache-2.0.

Score
62/100
Adoption (stars) 12/40
Maintenance 30/30
Framework (licence, registry, official) 20/30
Actively maintainedRemote server

What PipesHub does

According to its repository: “Permission-aware enterprise search and RAG over business apps such as Google Workspace, Microsoft 365, Slack and Jira.”

An MCP server gives an AI agent extra tools it calls during the conversation: the agent reads their description, decides to use them and gets the result back. PipesHub is listed under Memory and knowledge, a category of 250 servers in the directory, where it ranks #157 by stars.

Topics declared by the repository: ai-agents, claude, cursor, enterprise-search, rag, pipeshub.

Installing and connecting PipesHub

Distribution modes declared in the official MCP registry:

  • npm package (Node.js, usually started with npx)
  • remote server (streamable-http): you connect to it by URL, with nothing to install locally

Like any MCP server, you declare it in your client's configuration (Claude Desktop, Claude Code, Cursor, VS Code, Codex…): a name, the command that starts it or its URL, and any environment variables. The client then starts it and lists its tools. Project language: TypeScript.

Security: what to check

An MCP server runs code with the rights you give it, and the model reads its tool descriptions: a malicious or compromised server can hijack the agent. Read the code, or pick a maintained and widely used server, before connecting it.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to PipesHub. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on January 17, 2026, the pipeshub-ai/mcp-server repository has 17 stars and 7 forks, with 1 open issues. It has more stars than 35% of the servers in the directory. It received changes this month. Version published in the registry: 4.4.0 (October 22, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.

Context7Context7 : 63.6K63.6KHindsightHindsight : 53.4K53.4KCogneeCognee : 32.7K32.7KSkill SeekersSkill Seekers : 15.2K15.2KHonchoHoncho : 7.8K7.8KBasic memoryBasic memory : 4.3K4.3KNoteDiscoveryNoteDiscovery : 2.8K2.8KMemantoMemanto : 2.3K2.3KPipesHubPipesHub : 1717
GitHub stars of the most followed servers in the category (log scale); PipesHub in orange. Checked October 25, 2026.

Verdict

PipesHub is a reasonable choice; check the points below before connecting it.

Strengths

  • Active project: recent commit
  • Listed in the official MCP registry
  • Usable remotely, without installation
  • Permissive licence (Apache-2.0)

Frequently asked questions

How do I install PipesHub?

PipesHub is distributed as npm package (Node.js, usually started with npx) and a remote server. Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of pipeshub-ai/mcp-server.

Is PipesHub free?

The code is published under the Apache-2.0 licence and can be used free of charge.

Is PipesHub safe?

No risk signal found (system access, secrets, licence, abandonment). As with any MCP server, keep rights minimal and read the code before sensitive use.

Is it an official server?

Nothing says so: it is a project published by pipeshub-ai on GitHub. Check who maintains it before giving it access.

What are the alternatives to PipesHub?

In the same category: Context7, Basic memory, Hindsight, and Cognee. Context7 and Basic memory score higher on our grid.

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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score