Integrates with Google's Gemini API to provide AI-powered reflection and analytical capabilities through Google's language models
Connects to local Ollama instances to run open-source language models for reflection and analysis while maintaining full offline capability
Connects to OpenAI's API to leverage GPT models for reflection, differential diagnosis, and intelligent analysis of user notes and questions
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., "@Reflection MCP Serverreflect on our discussion about project priorities from yesterday"
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.
Reflection MCP Server
Part of the LXD MCP Suite — a cohesive set of MCP servers for learning experience design (coaching, Kanban, stories, and optional LLM adapters).
What it is
Lightweight reflection MCP server (stdio) that detects available providers and stores short local memories.
Why it helps
Optional tailoring/validation for other servers; stays small and safe. Works fully offline with local memory only.
Lightweight reflection and differential diagnosis MCP server.
Detects provider from environment/.env (OpenAI, Anthropic, Gemini, Ollama) and uses a lightweight local model if no network provider is available.
Stores short, bounded memories per
keyin.local_context/reflections/<key>.jsonl.Exposes MCP tools over stdio:
reflection_handshake(user_key, name)reflect(key, input)ask(key, question)note(key, note)memories(key, limit?)summarize(key)
Quickstart
# Run from a clone/checkout
python3 reflection_mcp/mcp_server.pyRegister with an MCP client (example)
Claude Desktop (config snippet):
{
"mcpServers": {
"reflection-mcp": {
"command": "python3",
"args": ["/absolute/path/to/reflection_mcp/mcp_server.py"],
"env": { "PYTHONUNBUFFERED": "1" }
}
}
}Environment variables
OpenAI:
OPENAI_API_KEY,OPENAI_BASE_URL(optional),OPENAI_MODEL(default:gpt-4o-mini)Anthropic:
ANTHROPIC_API_KEY,ANTHROPIC_BASE_URL(optional),ANTHROPIC_MODEL(default:claude-3-haiku-20240307)Gemini:
GOOGLE_API_KEY,GEMINI_BASE_URL(optional),GEMINI_MODEL(default:gemini-1.5-flash)Ollama:
OLLAMA_BASE_URLorOLLAMA_HOST,OLLAMA_MODEL(default:llama3.1:8b-instruct)
If no provider key is found or requests fail, the server falls back to a local lightweight reflector.
File layout
reflection_mcp/mcp_server.py: MCP stdio serverreflection_mcp/provider.py: provider detection + HTTP clientutils/reflection_memory.py: shared local memory store (JSONL)
Install (local PATH)
bash scripts/install_local.sh
export PATH="$HOME/.local/bin:$PATH" # add to shell profile for persistence
# Start server from anywhere
reflection-mcpRun at Login
macOS (launchd)
bash scripts/install_service_macos.sh
# Logs:
tail -f "$HOME/Library/Logs/reflection-mcp.out" "$HOME/Library/Logs/reflection-mcp.err"Linux (systemd user)
bash scripts/install_service_systemd.sh
systemctl --user status reflection-mcp.service
journalctl --user -u reflection-mcp.service -fLicense
Proprietary/internal by default. Add a license if open-sourcing.
Internal Use Only — not licensed for external distribution or hosting.
This server cannot be installed
Resources
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Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.