CLI tool for building production RAG systems from Markdown, CSV, and PDF documents using hybrid search (BM25 + vector) with OpenSearch. Features MCP server, Slack bot, Web UI, multi-source ingestion (local/S3/GitHub), and multi-provider embeddings (Bedrock/Gemini).
Last commit July 15, 2026, 120 days ago.
12 GitHub stars and 0 Honeystax upvotes. Copy the install, test the workflow, then decide if it earns a permanent slot.
You can test this quickly and remove it cleanly if it misses.
Starts at 6. Added: last commit 120 days ago +14, GitHub health 62/100 +8, no security policy +8, no contributing guide +4, no code of conduct +3.
AI Agent
Universal
Model
Gemini
Fastest way to find out if ragent belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
claude mcp add ragent -- npx ragentRun this first. You will know quickly if the workflow earns a permanent slot.
claude mcp remove ragentNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude.json └─ mcp_servers/ └─ ragent ← registers here
ragent is listed on Honeystax as a MCP Server for Universal, since June 24, 2026. Its code is at github.com/ca-srg/ragent, with 12 GitHub stars and 1 open issues. Last commit July 15, 2026, 120 days ago. GitHub's community health check gives it 62 out of 100.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 15, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.