Skip to main content
Glama

fetch_fetch

Extract readable text content from URLs by converting HTML pages to plain text for AI applications.

Instructions

[fetch] Fetch the text content of a URL. HTML pages are automatically converted to readable plain text. Use 'search' to find URLs; use 'fetch' to read a specific URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
max_charsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it fetches text content, automatically converts HTML to readable plain text, and implies it's a read operation (no mention of mutation). However, it lacks details on error handling, rate limits, authentication needs, or response format. The description adds some value but doesn't fully cover behavioral aspects.

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?

The description is appropriately sized and front-loaded, with two sentences that each earn their place. The first sentence states the core functionality, and the second provides usage guidelines. There is no wasted text, making it efficient and well-structured for quick comprehension.

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?

Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is reasonably complete. It covers the purpose, usage context, and basic behavior. The output schema likely handles return values, so the description doesn't need to explain them. However, it could improve by addressing parameters or error cases more explicitly.

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 0%, so the description must compensate. It mentions 'URL' and implies text content fetching, which aligns with the 'url' parameter, but doesn't explain 'max_chars' or provide any parameter details beyond the basic purpose. The description adds minimal semantic value over the schema, resulting in a baseline score.

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 clearly states the tool's purpose with a specific verb ('fetch') and resource ('text content of a URL'), and explicitly distinguishes it from the sibling 'search' tool. It provides the exact action (fetch text content), transformation (HTML converted to plain text), and differentiation (use 'fetch' for reading a specific URL vs. 'search' to find URLs).

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 provides explicit guidance on when to use this tool versus alternatives. It states 'Use 'search' to find URLs; use 'fetch' to read a specific URL,' which clearly defines the context and alternative tool. This gives the agent precise instructions on tool selection based on the task.

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/0-co/agent-friend'

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