streamlit-mcp 0.2.3

Serve an existing Streamlit app as an MCP server — agents drive it natively, no browser.

streamlit-mcp

Serve any Streamlit app as an MCP server. Agents introspect your app's widgets, set values, click buttons, and read the rendered output and session_state — natively, over MCP, with no browser automation.

pip install streamlit-mcp          # or run with no install via: uvx streamlit-mcp ...

# serve an app over MCP (stdio for local clients)
streamlit-mcp serve app.py
# ...or HTTP/SSE on loopback for local networked agents
streamlit-mcp serve app.py --transport http --port 8000

# drive it yourself from the terminal (same engine the agent uses)
streamlit-mcp inspect app.py
streamlit-mcp call app.py --set "Name=agent" --click "Save" --read

Streamlit has no callback graph — it reruns the whole script per interaction — so streamlit-mcp drives the app headlessly through Streamlit's own test runtime (streamlit.testing.v1.AppTest) and returns the semantic element tree, not pixels. Gradio and Dash already shipped native app-as-MCP; this fills the Streamlit gap.

Use it with an MCP client

Claude Desktop / Cursor — add to your MCP config (claude_desktop_config.json or .cursor/mcp.json):

{
  "mcpServers": {
    "streamlit-mcp": {
      "command": "uvx",
      "args": ["streamlit-mcp", "serve", "/absolute/path/to/your/app.py"]
    }
  }
}

Claude Code:

claude mcp add streamlit-mcp -- uvx streamlit-mcp serve /absolute/path/to/your/app.py

uvx runs the published package with no prior install. stdio (the default) is the right transport for local clients.

Tools exposed to agents

Tool	What it does
list_widgets / get_layout	introspect widgets (kind, label, value, constraints)
set_widget(identifier, value)	set a widget and rerun
click(identifier)	click a button and rerun
read_output()	the rendered element tree, agent-readable
get_state()	the app's session_state

Supported widgets (v1): text_input, number_input, text_area, slider, selectbox, multiselect, checkbox, radio, button, date_input. Unsupported elements (file_uploader, custom components, st.chat, fragments) are reported explicitly, never silently dropped.

Custom semantic tools

Beyond the per-widget tools, expose a higher-level named action by decorating a function with @mcp_tool in your app file:

import streamlit as st
from streamlit_mcp import mcp_tool

@mcp_tool
def reset_all():
    """Reset everything to defaults."""
    return {"ok": True}

st.text_input("Name")

streamlit-mcp serve app.py loads the app and exposes reset_all over MCP alongside the widget tools. The decorated function is called directly (it isn't a widget), so keep it self-contained.

Human ↔ agent parity

Everything an agent can do over MCP, a human can do via the CLI — both call the same engine. The read-only mode and widget allow-list guardrails apply identically to both surfaces.

Security / trust model

• app_path is executed as trusted code in the server process (that's how AppTest runs it). Only serve apps you trust.
• get_state / read_output expose the app's session_state to the caller — do not put secrets there.
• HTTP/SSE bearer auth is enforced. Pass --bearer-token <T> and every HTTP/SSE request must send Authorization: Bearer <T> — a missing or wrong token gets 401 before any tool runs. A non-loopback host is allowed only with a token set; without one, serve binds 127.0.0.1 only and refuses a non-loopback host (fail closed). stdio is local and unauthenticated.

License

MIT