LynxPrompt MCP
Browse, search, and manage AI configuration blueprints and prompt hierarchies via LynxPrompt
LynxPrompt-MCP
A tiny bridge that exposes any LynxPrompt instance as an MCP server, enabling LLMs to browse, search, and manage AI configuration blueprints.
What you get
| Type | What for | MCP URI / Tool id |
|---|---|---|
| Resources | Browse blueprints, hierarchies, and user info read-only | lynxprompt://blueprintslynxprompt://blueprint/{id}lynxprompt://hierarchieslynxprompt://hierarchy/{id}lynxprompt://user |
| Tools | Create, update, delete blueprints and manage hierarchies | search_blueprintscreate_blueprintupdate_blueprintdelete_blueprintcreate_hierarchydelete_hierarchy |
Everything is exposed over a single JSON-RPC endpoint (/mcp).
LLMs / Agents can: initialize -> readResource -> listTools -> callTool ... and so on.
Quick-start (Docker Compose)
services:
lynxprompt-mcp:
image: drumsergio/lynxprompt-mcp:latest
ports:
- "127.0.0.1:8080:8080"
environment:
- LYNXPROMPT_URL=https://lynxprompt.com
- LYNXPROMPT_TOKEN=lp_xxx
Security note: The HTTP transport listens on
127.0.0.1:8080by default. If you need to expose it on a network, place it behind a reverse proxy with authentication.
Install via npm (stdio transport)
npx lynxprompt-mcp
Or install globally:
npm install -g lynxprompt-mcp
lynxprompt-mcp
This downloads the pre-built Go binary from GitHub Releases for your platform and runs it with stdio transport. Requires at least one published release.
Local build
git clone https://github.com/GeiserX/lynxprompt-mcp
cd lynxprompt-mcp
# (optional) create .env from the sample
cp .env.example .env && $EDITOR .env
go run ./cmd/server
Configuration
| Variable | Default | Description |
|---|---|---|
LYNXPROMPT_URL | https://lynxprompt.com | LynxPrompt instance URL (without trailing /) |
LYNXPROMPT_TOKEN | (required) | API token in lp_xxx format |
LISTEN_ADDR | 127.0.0.1:8080 | HTTP listen address (Docker sets 0.0.0.0:8080) |
TRANSPORT | (empty = HTTP) | Set to stdio for stdio transport |
Put them in a .env file (from .env.example) or set them in the environment.
Testing
Tested with Inspector and it is currently fully working. Before making a PR, make sure this MCP server behaves well via this medium.
Example configuration for client LLMs
{
"schema_version": "v1",
"name_for_human": "LynxPrompt-MCP",
"name_for_model": "lynxprompt_mcp",
"description_for_human": "Browse, search, and manage AI configuration blueprints from LynxPrompt.",
"description_for_model": "Interact with a LynxPrompt instance that stores AI configuration blueprints. First call initialize, then reuse the returned session id in header \"Mcp-Session-Id\" for every other call. Use readResource to fetch URIs that begin with lynxprompt://. Use listTools to discover available actions and callTool to execute them.",
"auth": { "type": "none" },
"api": {
"type": "jsonrpc-mcp",
"url": "http://localhost:8080/mcp",
"init_method": "initialize",
"session_header": "Mcp-Session-Id"
},
"logo_url": "https://lynxprompt.com/logo.png",
"contact_email": "[email protected]",
"legal_info_url": "https://github.com/GeiserX/lynxprompt-mcp/blob/main/LICENSE"
}
Credits
LynxPrompt -- AI configuration blueprint management
MCP-GO -- modern MCP implementation
GoReleaser -- painless multi-arch releases
Maintainers
Contributing
Feel free to dive in! Open an issue or submit PRs.
LynxPrompt-MCP follows the Contributor Covenant Code of Conduct.
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