Local LLM MCP server
A Node.js MCP server that exposes utility and sample HRMS tools over Streamable HTTP with shared bearer-token authentication, enabling local LLM gateways to call them in read-only mode.
README
Local LLM MCP server
A trusted-backend MCP server built with Node.js and FastMCP. It exposes tools over the MCP Streamable HTTP transport at http://127.0.0.1:3333/mcp and authenticates every MCP request with one shared bearer token.
There is no OAuth, user login, or browser connect flow. Keep this service on localhost or a private network that only the gateway can reach: possession of the shared token grants access to every registered tool.
Run locally
Requires Node.js 22 or later.
npm install
cp .env.example .env
# Replace MCP_SERVICE_TOKEN in .env with a long random secret.
npm start
For development with file watching, use npm run dev. For a compiled production run, use npm run build followed by npm run start:prod.
The server defaults to HOST=127.0.0.1, PORT=3333, and the fixed endpoint /mcp. Bind to a private interface only when the gateway runs on another machine.
Tools
All current tools are named so the gateway exposes them in its default read_only mode:
get_server_time— returns the current UTC time as an ISO string.get_echo— returns a supplied message to verify tool arguments and results.list_examples— returns sample calls/tools and supports an optionallimit.list_hrms_employees— returns sample employees and supports optional department and employment-status filters. Its isolated mock data source can later be replaced with the real HRMS API.
X-User-Email is accepted when supplied and stored in the FastMCP session as userEmail. It is optional and is not currently used to authorize or scope tools.
Project structure
src/
├── index.ts # Process startup and shutdown
├── config.ts # Environment parsing and validation
├── server.ts # FastMCP server construction
├── auth/
│ └── service-token.ts # Shared bearer-token authentication
└── tools/
├── index.ts # Central tool-group registration
├── basic/
│ ├── index.ts
│ ├── get-server-time.ts
│ ├── get-echo.ts
│ └── list-examples.ts
└── hrms/
├── index.ts
├── list-employees.ts # MCP schema and execution adapter
├── sample-data.ts # Temporary mock data and filtering
└── types.ts
test/
├── index.ts # Test entrypoint
├── auth.test.ts
├── config.test.ts
└── hrms.test.ts
Each domain owns its tools and exports one registration function from its index.ts. The central src/tools/index.ts is the only place that connects tool groups to the server.
When the real HRMS API is available, add an src/integrations/hrms/ client and replace the call to listSampleEmployees inside list-employees.ts. Keep API credentials in environment variables, HTTP handling in the integration client, and the MCP parameter schema in the tool file.
For another domain, create src/tools/<domain>/, export register<Domain>Tools, and add that group to src/tools/index.ts. Use a read-style tool name (get_, list_, search_, and similar) when it should remain visible under the gateway's default read_only policy.
Connect the local LLM gateway
In /home/manoj/newlaptop/projects/python/local-ai-model-gateway/.env, set:
MCP_SERVER_URL=http://localhost:3333/mcp
MCP_AUTH_TOKEN=<the same value as this server's MCP_SERVICE_TOKEN>
MCP_TOOL_MODE=read_only
For write tools added later, switch to MCP_TOOL_MODE=allowlist and set MCP_TOOL_ALLOWLIST to exact comma-separated tool names, or deliberately use all. Restart the gateway after changing its environment.
With a valid gateway JWT, GET /v1/tools should list these tools with backend set to mcp. POST /v1/agent can then select and call them.
Test
npm test
npm run typecheck
For a manual protocol test, start the server and launch MCP Inspector:
npx @modelcontextprotocol/inspector http://localhost:3333/mcp
Configure the Inspector connection to send Authorization: Bearer <the value of MCP_SERVICE_TOKEN>. Missing or incorrect bearer credentials receive HTTP 401.
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