Skip to main content
Glama

read_local_image

Read a local image file and encode it to base64, enabling use in API requests or data URIs. Supports both base64 and data URI formats for flexible integration.

Instructions

Read a local image file and convert it to base64. WARNING: Returns the full base64 string which can be very large and slow to display. Use prepare_image instead for better performance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute path to the image file
return_formatNoFormat to return: base64 string or data URIbase64
Install Server

TDQS

A4.4/5.0
Behavior4/5

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 warns that the output can be 'very large and slow to display', which is a meaningful performance trait. It does not explicitly state that the operation is read-only, but 'read_local_image' and 'Read a local image file' strongly imply no side effects.

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?

Two sentences with no filler. The purpose is stated first, followed by the warning and the alternative recommendation, which is well-structured and efficient.

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

Completeness4/5

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

For a simple two-parameter read tool without an output schema, the description covers the core behavior, the performance caveat, and the alternative. It does not cover error cases or supported file formats, but those are not essential given the schema and the straightforward nature of the operation. Slightly more context about when to use data_uri vs base64 could improve it, but it is largely complete.

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 description coverage is 100%, with both file_path and return_format clearly described in the input schema. The description adds the base64 conversion context, but this mostly overlaps with the schema's default value. Since the schema already handles parameter meaning, a baseline of 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?

The description states a specific action ('Read a local image file') and the transformation ('convert it to base64'), making the tool's function immediately clear. It also distinguishes itself from the sibling prepare_image by warning about the large output and recommending the alternative.

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?

The description explicitly names the alternative tool (prepare_image) and gives the condition for choosing it ('for better performance'). This tells an agent when not to use this tool and what to use instead, which is exactly what this dimension requires.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bratcliffe909/segmind-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server