Skip to main content
Glama
V2-Digital

V2.ai Insights Scraper MCP

by V2-Digital

summarize_post

Generate AI-powered summaries of V2.ai Insights blog posts by specifying the post index to extract key content quickly.

Instructions

Returns a summary of the blog post at the specified index

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYes

Implementation Reference

  • The internal logic implementation of `_summarize_post` which performs the actual fetching and summarization of the blog post.
    def _summarize_post(index: int):
        """Returns a summary of the blog post at the specified index"""
        posts = fetch_blog_posts()
        if 0 <= index < len(posts):
            post = posts[index]
            summary = summarize(post["content"])
            return {
                "title": post["title"],
                "date": post["date"],
                "author": post["author"],
                "url": post["url"],
                "summary": summary,
            }
        else:
            return {"error": f"Invalid index. Available posts: 0 to {len(posts) - 1}"}
  • The registration of the `summarize_post` tool using the @mcp.tool decorator.
    def summarize_post(index: int):
        """Returns a summary of the blog post at the specified index"""
        return _summarize_post(index)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Returns a summary'), which implies it's non-destructive, but doesn't cover aspects like error handling (e.g., what happens if the index is invalid), performance characteristics, or authentication needs. This leaves significant gaps for an agent to understand how to use it effectively.

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 a single, direct sentence with zero wasted words. It front-loads the core purpose ('Returns a summary') and efficiently specifies the resource and parameter, making it easy to parse quickly.

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

Completeness2/5

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

Given the complexity of summarizing content, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the summary includes (e.g., length, format), potential limitations, or how it interacts with sibling tools. For a tool that likely involves processing blog posts, more context is needed to guide an agent effectively.

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?

The input schema has 0% description coverage, so the description must compensate. It adds meaning by specifying that the 'index' parameter refers to a blog post index, which clarifies beyond the schema's generic 'integer' type. However, it doesn't provide details like valid index ranges or how indices are assigned, leaving some ambiguity. Given the single parameter and low schema coverage, this is adequate but not comprehensive.

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 the tool's purpose with a specific verb ('Returns a summary') and resource ('blog post at the specified index'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_post_content' or 'search_blogs', which might also retrieve post information, so it falls short of a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives such as 'get_post_content' or 'search_blogs'. It mentions a specific index parameter but doesn't explain prerequisites like needing to know the index beforehand or how it relates to other tools that might list posts.

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/V2-Digital/v2-ai-mcp'

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