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Resource Schema Generator

Create an MCP Resource Schema. Define URI templates and metadata for resources exposed by your MCP server.

{
  "uri": "file://{path}",
  "name": "",
  "description": "",
  "mimeType": "text/plain"
}

How Resource Schema Generator Works

An MCP Resource Schema Builder is a specialized URI-engineering utility used to define the addressable "Data Nodes" in a Model Context Protocol server. This tool is essential for AI data engineers, backend developers, and system architects defining how a model accesses files, database rows, or API streams, ensuring that "Resource URIs" follow the standard template syntax (RFC 6570), and validating that resource metadata is correctly exposed for AI browsing.

The processing engine handles resource definition through a rigorous three-stage technical pipeline:

  1. Template Architecting: The tool identifies your URI Template Pattern. MCP supports variable-based URIs (e.g., file:///{path}/config.json) that allow a single resource definition to represent thousands of files.
  2. MIME Type Hardening: The engine applies Standard Media Type (IANA) logic:
    • Classification: Assigning text/plain, application/json, image/png, etc.
    • Model Compatibility: Tagging which resources are "Readable" vs. "Referenceable" by the LLM.
  3. Metadata Injection: The tool formats the output into the exact MCP ListResources Response Object, including the required name, description, and uriTemplate keys.
  4. Reactive Real-time Rendering: Your "Cloud/Local Resource Map" updates instantly as you modify URI variables or toggle data types.

The History of Resources: From Filesystems to Model Context

How AI "Reads Data" has evolved from simple file reading to structured protocol access.

  • The Shared Drive (1980s): Computers accessed data via mapped network drives. This was for humans, not AI.
  • REST Resources (2000): Roy Fielding introduced the Representational State Transfer (REST) model, making every data point a "Resource" at a URI.
  • The MCP Resource (2024): Anthropic standardized the Resource Pattern for AI. Unlike traditional APIs, MCP Resources are built specifically for discovery—allowing the AI to browse your database as if it were a file system. This builder Automates the setup of those connections, ensuring your data is "AI-Ready."

Technical Comparison: Resource Exposure Paradigms

Understanding how to "Map your Data" is vital for AI Retrieval Accuracy and Data Security.

Paradigm Benefit logic Workflow Impact
Static URI Simplicity Direct Link Low Speed
URI Template Scaleable Mapping RFC 6570 High Reach
Annotated File Human-Friendly metadata Accuracy
Direct Stream Real-time Data Event-Driven Depth
Filtered View Security Privacy Reliability

By using this tool, you ensure your MCP Resource Schemas are technically sound and discovery-optimized.

Security and Privacy Considerations

Your resource schema building is performed in a secure, local environment:

  • Local Logical Execution: All URI template generation and metadata formatting are performed locally in your browser. Your internal server structures and private file paths never touch our servers.
  • Zero Log Policy: We do not store or track your inputs. Your Internal Data Schemas and Private URI Mappings remain entirely confidential.
  • W3C Security Compliance: The tool operates within the standard browser sandbox, ensuring no interaction with your local file system or Private Metadata.
  • Privacy First: To maintain absolute Data Privacy, the tool functions as an anonymous utility.

How It's Tested

We provide a high-fidelity engine that is verified against Latest MCP resource specification.

  1. The "URI Compliance" Pass:
    • Action: Input an invalid URI structure (e.g., missing slashes).
    • Expected: The Audit engine must warn you that MCP resources require valid URI schemes (like file:// or postgres://).
  2. The "Variable Syntax" Check:
    • Action: Use {} curly braces in the template incorrectly.
    • Expected: The tool must correctly validate the RFC 6570 syntax and highlight any malformed variable placeholders.
  3. The "MIME Type" Test:
    • Action: Leave the MIME type blank.
    • Expected: The tool must incorrectly suggest a default (e.g., text/plain) to ensure the AI knows how to parse the data.
  4. The "Metadata Polish" Defense:
    • Action: Input a repetitive description.
    • Expected: The tool must advise on unique descriptions to help the AI distinguish between multiple resources.

Frequently Asked Questions

In MCP, a resource is Read-Only Data. It could be a CSV file, a log tail, or the current weather returned by an API. If the AI needs to Write data, you should use a "Tool" instead.