How do I configure the LLM backend?
Edit `cp_agent.config.yaml` to set the LLM backend (e.g., Ollama or OpenAI) and adjust system prompts, MCP server connections, and tool availability.
@alwalt
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"osdr_mcp_server": {
"command": "python",
"args": [
"first_example/main.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
This project demonstrates how to integrate MCP agents with custom tools for interacting with NASA’s Open Science Data Repository (OSDR). It includes working examples of agent workflows that fetch, analyze, and summarize biological data using the Model Context Protocol (MCP).
Clone the repository, install dependencies with pip install -r requirements.txt, then run an example (e.g., python first_example/main.py) or launch the MCP server directly (python osdr_mcp/main_simple.py). Configuration is done via cp_agent.config.yaml.
osdr_fetch_metadata and osdr_find_by_organismosdr_viz_toolsEdit `cp_agent.config.yaml` to set the LLM backend (e.g., Ollama or OpenAI) and adjust system prompts, MCP server connections, and tool availability.
From the repo root, run `python first_example/main.py`, `python second_example/main.py`, or `python third_example/main.py` depending on the desired workflow.
The `osdr_mcp` package provides `osdr_fetch_metadata` and `osdr_find_by_organism`; additional tools like RNA analysis are in `osdr_viz_tools`.
All biological data is fetched from NASA’s Open Science Data Repository via its public API.
Python and the packages listed in `requirements.txt`. Optionally, an LLM backend like Ollama or an OpenAI API key must be configured.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
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