Skip to main content
Glama

files-read

files-read

Retrieve file content from storage. Images display directly; other files return base64-encoded data or plain text based on encoding option.

Instructions

Reads file content from storage. Images (PNG, JPEG, GIF, WebP, SVG) are returned as native MCP image content blocks that LLMs can view directly. Non-image files return base64-encoded content by default, or plain text if encoding='text'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
encodingNoOutput encoding: 'base64' (default, for binary files) or 'text' (for text files). Ignored for images.
item_idYesFile item ID (@rid format)
Behavior3/5

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

Without annotations, the description reveals important behavior: images become native MCP image blocks, non-images use base64 or text. But it omits details on error handling, permissions, size limits, or truncation, leaving gaps.

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, front-loaded with the core action, no unnecessary words. Every sentence contributes meaningful information.

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?

With no output schema, the description explains return types for images and non-images. It covers key behavior but misses potential edge cases like large files or invalid IDs, though for a simple tool this is mostly sufficient.

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

Parameters4/5

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

Schema coverage is 100%, and the description adds value by noting that the encoding parameter is ignored for images, which is not in the schema. This clarifies semantics beyond the structured fields.

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

Purpose4/5

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

The description clearly states that the tool reads file content from storage and distinguishes between image and non-image handling. However, it does not differentiate from sibling tools like files-find_by_name or files-list_versions, though their purposes are distinct.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives, nor prerequisites or exclusions. The description lacks context for tool selection.

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

Install Server

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/mstang/casemgr-mcp'

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