MCP server for Source Cooperative auto-discovery and data exploration
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# Source Cooperative MCP Server [](https://github.com/yharby/source-coop-mcp/actions) [](https://pypi.org/project/source-coop-mcp/) [](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) **Discover and access 800TB+ of geospatial data through AI agents.** An MCP (Model Context Protocol) server for [Source Cooperative](https://source.coop) - a collaborative repository with datasets from Maxar, Harvard, ESA, USGS, and 90+ organizations. --- ## 🏗️ Architecture Overview ```mermaid graph TB subgraph "AI Clients" A1[Claude Desktop] A2[Claude Code] A3[Cursor] A4[Cline] A5[Zed] A6[Continue.dev] end subgraph "MCP Server" MCP[Source Cooperative MCP<br/>FastMCP + obstore] end subgraph "6 Available Tools" T1[list_accounts<br/>94+ orgs] T2[list_products<br/>hybrid S3+API] T3[get_product_details<br/>+ README] T4[list_product_files<br/>tree mode] T5[get_file_metadata<br/>no download] T6[search<br/>hybrid fuzzy] end subgraph "Data Sources" S1[HTTP API<br/>source.coop/api] S2[S3 Direct<br/>opendata.source.coop] end A1 -->|JSON-RPC| MCP A2 -->|JSON-RPC| MCP A3 -->|JSON-RPC| MCP A4 -->|JSON-RPC| MCP A5 -->|JSON-RPC| MCP A6 -->|JSON-RPC| MCP MCP --> T1 MCP --> T2 MCP --> T3 MCP --> T4 MCP --> T5 MCP --> T6 T1 --> S2 T2 --> S1 T2 --> S2 T3 --> S1 T3 --> S2 T4 --> S2 T5 --> S2 T6 --> S1 style MCP fill:#4CAF50,stroke:#2E7D32,stroke-width:3px,color:#fff style S1 fill:#2196F3,stroke:#1976D2,stroke-width:2px,color:#fff style …
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