Camel-toolkits-mcp
A lightweight server that exports CAMEL framework toolkits as MCP-compatible tools.
README
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
Installation
You can install the package directly from PyPI:
pip install camel-toolkits-mcp
Or 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:
pytest
Contributing
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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.