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Semantic Cache MCP

by CoderDayton
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Read Image

read_image

Read an image file so the model can view it, returning base64 image data with metadata. Detects format by file contents, accepts PNG, JPEG, GIF, TIFF, BMP, WebP, and rejects non-images or oversized files.

Instructions

Read an image file so the model can see it.

Returns an MCP image block (base64 data + mime type) plus a small JSON metadata sidecar (size, mime). Use this only when the model needs to view the image; for text or any other file type use read.

The format is detected from the file's magic bytes, not its extension, so a mis-named image still works and a non-image (e.g. text saved as .png) is rejected. Supports PNG, JPEG, GIF, TIFF, BMP, and WebP. Images are never cached — every call re-reads from disk. Oversized images are rejected before encoding; the cap is SCMCP_MAX_IMAGE_BYTES (default 5 MiB), bounded by Anthropic's ~5 MB upload limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesImage file path (absolute, or relative to the project root).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "mime": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "default": null,
-      "title": "Mime"
-    },
-    "path": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "default": null,
-      "title": "Path"
-    },
-    "size": {
-      "anyOf": [
-        {
-          "type": "integer"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "default": null,
-      "title": "Size"
-    },
-    "truncated": {
-      "anyOf": [
-        {
-          "type": "boolean"
-        },
-        {
-          "type": "null"
-        }
-      ],
-      "default": null,
-      "title": "Truncated"
-    }
-  },
-  "title": "ReadImageResponse",
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changedv0.5.1
    • addedInput schema / properties / path / description
      Added value: +"Image file path (absolute, or relative to the project root)."
  3. Addedv0.4.8

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals the return shape, magic-byte detection, rejection of non-images, supported formats, no-caching behavior, and the size cap. These traits are not inferable from the schema or title, making this strong transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short paragraphs each earn their place: purpose, return value, usage routing, and behavioral caveats. Key information is front-loaded and there is no filler or tautology.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no annotations and no output schema, the description supplies the output format, error behavior, supported formats, cache policy, and size bound. An agent has everything needed to decide whether and how to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter, including absolute/relative path semantics. The description doesn't add parameter-level detail, but none is needed given the schema already fully documents `path`. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('read'), resource ('image file'), and purpose ('so the model can see it'). It clearly separates itself from sibling `read` by restricting to images. This is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this only when the model needs to view the image; for text or any other file type use `read`.' This gives both a clear condition and an alternative tool. Additional format and size notes reinforce correct selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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