AI & Memory MCP Server

MCP Ragdocs

Name: MCP Ragdocs
Author: hannesrudolph

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context

Scan found nothing by hannesrudolph256MITTypeScriptIntermediatestdio

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Install

No auto-install command available for this server.

Check the GitHub repository for setup instructions

Safety Report

83% Scan found nothing

Scanned 5 months ago

5 passed 1 failed

Security

Authentication

details

Authentication detected: env_api_key

Pass

CORS Policy

details

stdio transport — CORS not applicable

N/A

Rate Limiting

details

No rate limiting mechanism detected

Info

Known CVEs

details

No known CVEs in dependencies

Pass

Code Quality

Dependency Audit

details

No known vulnerable dependencies detected

Pass

Dangerous Patterns

details

No dangerous code patterns detected

Pass

License

details

License: MIT

Pass

Community

Maintenance Status

details

Last commit over 1 year(s) ago

Fail

Learn about our security methodology →

Frequently Asked Questions

What is MCP Ragdocs?

Is MCP Ragdocs safe to use?

We cannot tell you that, and nobody scanning at this scale can. What we did in March 2026 was shallow-clone MCP Ragdocs and run five keyword searches over its source: auth identifiers, CORS configuration, rate-limit identifiers, the dependency manifest against a hardcoded list of 18 known-vulnerable packages, and unguarded eval/exec calls. None of them matched. A text search cannot follow a variable, judge intent, or tell you what a server does once it is running, so "nothing matched" is not "safe". What the scan does and does not cover is written out at /mcp/security.

What are alternatives to MCP Ragdocs?

Similar MCP servers include Context7, Cognee, Hindsight. Each serves a similar purpose but may differ in features, language, and compatibility.