engine
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., "@engineget system information"
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.
engine
A self-owned, model-agnostic AI agent client whose core is a native, host-agnostic plugin
system. Adding a tool — from a tiny helper to the full scribe transcriber — is one small act,
and the same tool works for both you (a REPL command) and the agent (a model tool). Plain
line-REPL by design: no fullscreen TUI, so Polish input, trackpad scroll and text selection just
work. Runtime is stdlib-only and portable (macOS now, Linux/3090 later).
Layout
engine/— core:config,backends(the model interface),plugins(contract + discovery),agent(the loop),repl(the client),cli(bare-shell host adapter).plugins/— drop-in plugins:sysinfo(tiny),scribe(big). Add one = add a file here.tests/— pytest suite (deterministic, no network).smoke/— live checks against a real model (Ollama).tools/check_polish_input.py— a Polish-keyboard input check.
Related MCP server: Test MCP Server
Run
# REPL (talks to qwen3:8b via Ollama by default):
PYTHONPATH=. .venv/bin/python -m engine.repl
# force the deterministic mock model instead:
ENGINE_BACKEND=mock PYTHONPATH=. .venv/bin/python -m engine.repl
# run a plugin straight from the shell (no model):
PYTHONPATH=. .venv/bin/python -m engine.cli sysinfo
PYTHONPATH=. .venv/bin/python -m engine.cli scribe --helpAdd a plugin (zero core edits)
Create plugins/hello.py:
from engine.plugins import SimplePlugin
PLUGIN = SimplePlugin("hello", "say hi",
{"type": "object", "properties": {"input": {"type": "string"}}},
lambda a: "hi " + str(a.get("input", "")))It is now a REPL command (/hello), a CLI command, and a tool the agent can call.
Swap the model (one value)
ENGINE_BACKEND=ollama|mock|anthropic (+ ENGINE_OLLAMA_MODEL / ENGINE_ANTHROPIC_MODEL). A new
provider is one branch in engine/backends.py:get_backend. (anthropic is code-complete + unit-tested
for wire format; going live needs ANTHROPIC_API_KEY.)
Use the plugins inside Claude Code (MCP)
The same plugins are exposed to Claude Code via a hand-rolled MCP stdio server (stdlib, zero deps):
# from the repo root:
claude mcp add engine -- "$PWD/.venv/bin/python" -m engine.hosts.mcp_serverThen Claude Code can call sysinfo / calc / scribe as tools — the identical plugins your REPL uses.
Tests
.venv/bin/python -m pytest . # 36 deterministic tests
.venv/bin/python smoke/ollama_agent_smoke.py # live: a real model calls a plugin
.venv/bin/python smoke/filter_spike.py # Phase-2 taste: bge-m3 separates real vs junk (toy)Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/NieLubieRudej/engine'
If you have feedback or need assistance with the MCP directory API, please join our Discord server