Install
$ agentstack add mcp-simonw-llm-mcp-client ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README — it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming — see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps — measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
llm-mcp-client
[](https://pypi.org/project/llm-mcp-client/) [](https://github.com/simonw/llm-mcp-client/releases) [](https://github.com/simonw/llm-mcp-client/actions/workflows/test.yml) [](https://github.com/simonw/llm-mcp-client/blob/main/LICENSE)
Access tools from MCP servers as LLM tools
Installation
Install this plugin in the same environment as LLM.
llm install llm-mcp-client
Usage
This plugin registers a toolbox called MCP which connects to an MCP server, discovers the tools it exposes and makes them available as LLM tools.
Pass the URL of an MCP server to the toolbox:
llm -T 'MCP("https://example.com/mcp")' 'Ask something that needs a tool' --td
The --td option shows details of the tool calls as they execute.
It works in llm chat too:
llm chat -T 'MCP("https://example.com/mcp")'
Templates
You can save an MCP to a named LLM template like this:
llm -T 'MCP("https://datasette.simonwillison.net/-/mcp")' --save blog
Now you can query it without specifying the full tool definition like this:
llm -t blog 'count entries and notes'
Protocol modes
By default the client negotiates the protocol automatically. You can force a specific mode with the mode= argument:
# Force modern stateless MCP:
llm -T 'MCP("https://example.com/mcp", mode="stateless")' '...'
# Force the legacy initialize handshake:
llm -T 'MCP("https://example.com/mcp", mode="legacy")' '...'
Tool name prefixes
If you are using tools from more than one server and their names might clash, give each server a prefix:
llm -T 'MCP("https://one.example.com/mcp", prefix="one_")' \
-T 'MCP("https://two.example.com/mcp", prefix="two_")' '...'
Python API
import llm
from llm_mcp_client import MCP
model = llm.get_model("gpt-4.1-mini")
result = model.chain(
"Ask something that needs a tool",
tools=[MCP("https://example.com/mcp")],
).text()
Tool results containing MCP image or audio content are returned to the model as LLM attachments. An MCP error result raises llm_mcp_client.MCPToolError, which LLM passes back to the model as an error message.
Development
To set up this plugin locally, first checkout the code. Then run the tests with uv:
cd llm-mcp-client
uv run pytest
To run LLM with your in-development plugin:
uv run llm --help
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: simonw
- Source: simonw/llm-mcp-client
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.