This simple Model Context Protocol (MCP)
client demonstrates the use of MCP server tools by LangChain ReAct Agent.
It leverages a utility function convert_mcp_to_langchain_tools() from
langchain_mcp_tools.
This function handles parallel initialization of specified multiple MCP servers
and converts their available tools into a list of LangChain-compatible tools
(List[BaseTool]).
LLMs from Anthropic, OpenAI and Groq are currently supported.
A typescript version of this MCP client is available
here
Prerequisites
- Python 3.11+
- [optional]
uv (uvx)
installed to run Python package-based MCP servers
- [optional] npm 7+ (
npx)
to run Node.js package-based MCP servers
- API keys from Anthropic,
OpenAI, and/or
Groq
as needed
Setup
-
Install dependencies:
make install
-
Setup API keys:
cp .env.template .env
- Update
.env as needed.
.gitignore is configured to ignore .env
to prevent accidental commits of the credentials.
-
Configure LLM and MCP Servers settings llm_mcp_config.json5 as needed.
- The configuration file format
for MCP servers follows the same structure as
Claude for Desktop,
with one difference: the key name
mcpServers has been changed
to mcp_servers to follow the snake_case convention
commonly used in JSON configuration files.
- The file format is JSON5,
where comments and trailing commas are allowed.
- The format is further extended to replace
${...} notations
with the values of corresponding environment variables.
- Keep all the credentials and private info in the
.env file
and refer to them with ${...} notation as needed.
Usage
Run the app:
make start
It takes a while on the first run.
Run in verbose mode:
make start-v
See commandline options:
make start-h
At the prompt, you can simply press Enter to use example queries that perform MCP server tool invocations.
Example queries can be configured in llm_mcp_config.json5