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Langflow

Visual, low-code agent builder — GUI-based MCP client, no code required.

Langflow is a visual, drag-and-drop tool for building agentic/RAG flows — real GUI-based MCP client support, both a local server-start-command and a remote HTTP/SSE URL. Verified against a real installation.

Local (stdio)

In Langflow: Settings → MCP Servers → Add MCP Server (or the MCP icon in the flow editor sidebar), using the server start command option:

Prefer a fixed, pinned install over uvx's on-demand cache? Install into a virtual environment outside ~/Documents (pip install 'spomory[llm,embedding,mcp]'), then set Command to that venv's bin/memory-core-mcp directly.

Where do these environment variables come from?

LLM_API_KEY is your key for whichever OpenAI-compatible provider you use for extraction — OpenAI, DeepSeek, Qwen, and others all work. LLM_BASE_URL and LLM_MODEL default to OpenAI if you leave them out; swap them to point at DeepSeek, Qwen, or any other OpenAI-compatible provider, or a fully local server (Ollama, vLLM, llama.cpp, MLX):

export LLM_API_KEY=...
export LLM_BASE_URL=https://api.deepseek.com   # optional, defaults to OpenAI
export LLM_MODEL=deepseek-v4-flash             # optional, defaults to gpt-4o-mini
export EMBEDDING_MODEL=BAAI/bge-m3             # optional, defaults to bge-m3
Full local setup guide, including the macOS ~/Documents gotcha →

Langflow's MCP docs →

Cloud (API key)

Same Add MCP Server dialog, using the HTTP/SSE URL option instead:

Verified against a real Langflow installation, resolving to the same account/memory graph as every other client on this page.

Where does <your key> come from?

Get one instantly with curl — fine for your own testing:

curl -X POST https://api.yliuai.com/users/register \
  -H "Content-Type: application/json" \
  -d '{"email": "you@example.com"}'
# the api_key in the response (starts with mck_) is shown only this once -- save it

That hands you a key with no proof you control the email — fine for testing, but for real use, get one through the email-confirmation form instead, which actually verifies the address.

Get a verified key on the Cloud & Apps page →

Langflow's MCP docs →

Make it actually get used

Connecting the tools doesn't mean your client reaches for them on its own — it needs to be told to call search_memory before answering and add_memory after you share something worth keeping. SKILL.md is a short instructions file that does that. How you load it is specific to each client: some auto-discover a skills folder the same way Claude Code does, others only have a custom-instructions or system-prompt field instead. Verified for this one:

Langflow has no file-based skills convention — paste SKILL.md's content into the Agent component's "Agent Instructions" field in the flow editor instead.

SKILL.md on GitHub →