Hermes Atlas MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Hermes Atlas MCP Serversearch for memory persistence tools"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
πΊοΈ Hermes Atlas MCP Server
MCP server for the Hermes Atlas ecosystem directory β gives AI agents instant access to 169+ quality-filtered tools, skills, plugins, and integrations for Hermes Agent.
Why?
Hermes Agent has a massive and growing ecosystem. This MCP server turns that ecosystem into instant expandability β agents can discover, compare, and recommend tools without leaving their conversation.
Related MCP server: AgentHotspot MCP Server
Quick Start
Add to your MCP client config:
{
"mcpServers": {
"hermes-atlas": {
"command": "npx",
"args": ["hermes-atlas-mcp"]
}
}
}Or with Docker/stdio:
{
"mcpServers": {
"hermes-atlas": {
"command": "node",
"args": ["/path/to/hermes-atlas-mcp/dist/index.js"]
}
}
}Tools
Tool | Description | Example |
| Full-text search across 169 repos |
|
| Browse 12 ecosystem categories |
|
| Detailed repo info + AI summary |
|
| Match tools to your use case |
|
| Trending/rising repos this week |
|
| Curated lists overview |
|
| Specific curated list with per-repo descriptions |
|
| Aggregate stats, category breakdown, latest version |
|
| RAG over research knowledge base (requires embeddings) |
|
Optional: Local Embeddings
The ask_atlas tool provides RAG-powered answers grounded in 27 research files (6,500+ chunks) covering Hermes Agent installation, architecture, skills system, deployment, and best practices.
Install the embeddings (~70MB) separately:
npx hermes-atlas-mcp install-embeddings
# or equivalently:
npx hermes-atlas-installThe server auto-detects the embeddings at startup and adds the ask_atlas tool when available. Without embeddings, all other tools work perfectly using the summaries index.
How It Works
ββββββββββββββββββββββββββββββββββββββββββββββ
β hermes-atlas-mcp β
β β
β ββββββββββββ ββββββββββββββββ β
β β repos β β summaries β β
β β (169) β β (AI-generatedβ β bundled β
β ββββββ¬ββββββ β per-repo) β or fetchedβ
β β ββββββββββββββββ β
β ββββββ΄βββββββββββββββββββββββ β
β β lists, featured, stats β β cached β
β βββββββββββββββββββββββββββββ (4hr TTL) β
β β
β βββββββββββββββββββββββββββββ optional β
β β chunks.json (70MB) β β install β
β β RAG knowledge base β separatelyβ
β βββββββββββββββββββββββββββββ β
ββββββββββββββββββββββββββββββββββββββββββββββ
β
stdio (MCP)Zero-config: Works immediately with no API keys needed
Offline-capable: Bundled data works without network; fresh data fetched in background
Light: Core data is ~300KB; embeddings are opt-in at 70MB
Fast: Full-text search and recommendations complete in <50ms
Data Sources
All data sourced from ksimback/hermes-ecosystem β a community-curated directory security-reviewed before inclusion.
File | Size | Content |
| 60KB | 169 repos β owner, name, description, stars, category, official flag |
| 189KB | AI-generated summaries + highlights per repo |
| 2KB | 6 curated lists (best memory, top skills, deployment, etc.) |
| 26KB | Per-repo descriptions within each curated list |
| 241B | Currently featured/trending repos |
| 374B | Latest Hermes Agent version |
| 70MB | 6,554 research chunks with pre-computed embeddings (optional) |
Development
git clone https://github.com/your-user/hermes-atlas-mcp.git
cd hermes-atlas-mcp
npm install
npm run build
# Test interactively
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"0.1"}}}' | npm start
# Watch mode
npm run devLicense
MIT. Data sourced from hermes-ecosystem (MIT/CC BY 4.0).
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