This simple
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
(
LLMs from Anthropic, OpenAI and Groq are currently supported.
A typescript version of this MCP client is available here
- 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
-
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.
- Update
-
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 tomcp_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.
- The configuration file format
for MCP servers follows the same structure as
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