Camel-toolkits-mcp
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Camel-toolkits-mcplist all available CAMEL toolkits"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CAMEL Toolkits MCP
A lightweight server that exports CAMEL framework toolkits as MCP-compatible tools.
Overview
This project bridges the gap between the CAMEL AI framework's toolkit ecosystem and MCP (Model Control Protocol) compatible clients. It allows you to dynamically load and expose any Camel toolkit as an MCP server, making these tools available to a wide range of LLM-based applications.
Key features:
Dynamically discover and list available CAMEL toolkits
Load and execute toolkit functions at runtime
Seamless conversion of CAMEL toolkit functions to MCP-compatible tools
Related MCP server: mcpscope
Installation
You can install the package directly from PyPI:
pip install camel-toolkits-mcpOr install from source:
git clone https://github.com/jinx0a/camel-toolkits-mcp.git
cd camel-toolkits-mcp
pip install -e .Config with MCP clients
Using with uvx
You can easily configure uvx to run the CAMEL toolkits server like this:
{
"mcpServers": {
"camel-toolkits": {
"command": "uvx",
"args": [
"camel-toolkits-mcp"
],
"env": {
"OPENAI_API_KEY": "your-openai-key",
"NOTION_TOKEN": "your-notion-token",
"..." : "..."
}
}
}
}Local Development Configuration
If you're developing this package locally, you can configure UVX to use your development version:
{
"mcpServers": {
"camel_toolkits_mcp": {
"command": "/path/to/python",
"args": [
"/path/to/camel_toolkits_mcp/server.py"
],
"env": {
"OPENAI_API_KEY": "your-openai-key",
"NOTION_TOKEN": "your-notion-token",
"..." : "..."
}
}
}
}Available Tools
The server exposes the following MCP-compatible tools:
get_toolkits_list(): Lists all available CAMEL toolkits with their descriptionslist_toolkit_functions(toolkit_name, include_methods=True): Lists all functions available in a specific toolkitexecute_toolkit_function(toolkit_name, function_name, toolkit_params=None, function_args=None): Executes a specific function from a toolkit
Example: Using Tools
# First, discover available toolkits
toolkits = get_toolkits_list()
print(toolkits) # Shows all available toolkits
# List functions in a specific toolkit (e.g., NotionToolkit)
functions = list_toolkit_functions(toolkit_name="NotionToolkit")
# Execute a toolkit function
result = execute_toolkit_function(
toolkit_name="NotionToolkit",
function_name="search_pages",
toolkit_params={"notion_token": "your-notion-token"},
function_args={"query": "meeting notes"}
)Architecture
The router works by:
Scanning the CAMEL framework's toolkit directory
Analyzing each toolkit class to detect its tools and API requirements
Creating proper MCP-compatible wrappers for each tool function
Exposing these functions through the FastMCP server
Supported Toolkits
This server supports all toolkits in the CAMEL framework, including:
NotionToolkit
OpenAIToolkit
WebSearchToolkit
And many more...
API Key Management
For toolkits requiring API keys (like Notion, OpenAI, etc.), you should provide them in the environment variables when configuring the MCP server.
Development
To set up a development environment:
pip install -e ".[dev]"Run tests:
pytestContributing
Contributions are welcome! The project uses GitHub Actions for CI/CD:
Tests are run automatically on pull requests
New releases are automatically published to PyPI when a GitHub release is created
License
This project is licensed under the MIT License - see the LICENSE file for details.
This server cannot be deployed
Maintenance
Related MCP Connectors
MCP server for progressive tool usage at any scale (see https://klavis.ai)
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