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339,430 tools. Last updated 2026-07-30 07:08

"GDAL" matching MCP tools:

  • Find all subclasses of a given class recursively to assess impact of interface changes. Handles multi-level inheritance and resolves ambiguous class names with file path.
    MIT
  • Submit multiple queries for asynchronous batch processing with approximately 50% cost discount. Queries run within 24 hours; results are retrieved after completion.
    MIT
  • Retrieve extracted text results from a completed batch job. Use the batch job name to access responses keyed by custom_id.
    MIT
  • Submit a single independent question to Gemini without maintaining session history. Suitable for one-off lookups or batch queries where context is unnecessary.
    MIT

Matching MCP Servers

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    Exposes GDAL/Rasterio operations to AI agents with a reflection middleware that requires structured justification before executing operations whose methodology matters.
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    72
    MIT
  • A
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    An MCP server providing geospatial analysis tools for raster and vector data, integrated with a reflection system that requires AI agents to justify their methodological decisions. It enables accurate mapping and spatial operations by ensuring reasoned choices for coordinate systems, resampling, and data transformations.
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    72
    MIT
  • Retrieve all FileSearch stores with document counts and sizes. Monitor storage usage and manage your stores.
    MIT
  • Retrieve all accessible Gemini models, grouped by their supported actions like content generation or embedding.
    MIT
  • Execute Python code in a sandboxed environment using Gemini. Captures stdout, stderr, and execution results for analysis.
    MIT
  • Create a semantic search store for code files. Upload files into the store, and Gemini automatically searches them during code analysis.
    MIT
  • Retrieve the current status of a batch job by providing its name.
    MIT
  • Remove a completed batch job that has ended (succeeded, failed, or cancelled) by specifying its name.
    MIT
  • Cache large files (>32k tokens) with Gemini to reuse context across multiple turns, reducing processing overhead. Specify file URIs and model version.
    MIT
  • Upload a file to a FileSearch store to enable semantic search. Files are chunked and embedded for retrieval.
    MIT
  • Cancel a running batch job while preserving already-completed requests.
    MIT
  • Analyze a codebase by asking questions. Gemini autonomously reads files, lists directories, and searches code to provide answers, eliminating the need to pre-read files.
    MIT
  • Retrieve recent batch jobs processed by the AI agent, with configurable result limit for efficient review.
    MIT
  • List all layers in a spatial data source including FileGDB, Shapefile, GeoJSON, and more. Returns layer name, geometry type, feature count, and CRS for each.
    MIT
  • Perform web searches and receive formatted results (titles, URLs, snippets) using Gemini's built-in Google Search.
    MIT