🧠 OSDR MCP Server + Agents

by alwalt

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Description

# 🧠 OSDR MCP Server + Agents This repo 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…

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Author: alwalt
Downloads: 168
Categories: Other

- Exposes custom MCP tools: osdr_fetch_metadata and osdr_find_by_organism
- Includes additional RNA analysis tools in osdr_viz_tools
- Three example agent workflows for different integration levels
- Configurable LLM backend (Ollama, OpenAI) and MCP server connections
- Multi-agent pipeline: fetch, quantitative analysis, and summary writing

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name 🧠 OSDR MCP Server + Agents

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "\ud83e\udde0 osdr mcp server + agents": {
            "osdr_mcp_server": {
                "command": "python",
                "args": [
                    "first_example/main.py"
                ]
            }
        }
    }
}

McpServers

{
    "osdr_mcp_server": {
        "command": "python",
        "args": [
            "first_example/main.py"
        ]
    }
}

🧠 OSDR MCP Server + Agents

This repo 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).

📦 What’s Inside

`osdr_mcp/`

Custom MCP server exposing tools for interacting with OSDR data: - osdr_fetch_metadata: Fetches metadata for a given OSDR dataset - osdr_find_by_organism: Filters studies by organism - Additional tools (e.g. RNA analysis) live in osdr_viz_tools

`first_example/`

A simple agent that uses two official MCP servers: - mcp-server-fetch (headless browser) - mcp-server-filesystem

This agent gathers information and generates a tweet-sized summary.

`second_example/`

Similar to first_example but connects to a custom MCP server defined in osdr_mcp/main_simple.py. Demonstrates how to plug in domain-specific tools like OSDR metadata fetchers.

`third_example/`

A full multi-agent workflow: 1. Fetch Agent – Grabs OSD study metadata 2. Quant Analysis Agent – Downloads RNA count data and creates a bar plot 3. Summary Writer Agent – Generates a markdown report summarizing the analysis

Uses custom MCP servers:
- osdr_data_fetch
- osdr_viz_tools

⚙️ Configuration

The cp_agent.config.yaml file controls:
- LLM backend (e.g. Ollama, OpenAI)
- MCP server connections
- Tool availability
- System prompts / metadata

🚀 Getting Started

1. Clone this repo
2. Install dependencies:

   pip install -r requirements.txt

3. Run an example:

   python first_example/main.py

Or launch the MCP server directly:

python osdr_mcp/main_simple.py

🧩 Integration Notes

This architecture is built for flexibility. You can toggle between document Q&A, RAG search, or custom analysis tools. A mode switch or UI toggle is ideal for user-facing integration. Support for Milvus-based RAG via MCP is on the roadmap.

📚 Resources

- Model Context Protocol
- NASA OSDR API

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

🧠 OSDR MCP Server + Agents

📦 What’s Inside

osdr_mcp/

first_example/

second_example/

third_example/

⚙️ Configuration

🚀 Getting Started

🧩 Integration Notes

📚 Resources

Install

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`osdr_mcp/`

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