Medium Blog MCP Server

by Navneet1710

Overview Schema Source Related Servers Discussions Admin

Python

Local

Generate Full Content

generate_full_content

Generate a complete blog post in markdown from an outline and research, then save it as a draft.

Instructions

Generate complete blog post - Claude Desktop will write the blog based on outline

This tool provides the outline and research context. Claude (you) should:

Review the approved outline and research
Write the complete blog post in markdown
Call save_draft() with the generated content

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>"
    },
    "name": "generate_full_content"
  }
}

Input Schema

Name	Required	Description	Default
`session_id`	Yes	Active session ID

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

The description transparently discloses that the tool triggers a call to save_draft() with generated content, which is a side effect. It also indicates that it only uses the outline and research context, with no hidden destructive actions.

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 concise and well-structured with a clear header and numbered steps, avoiding unnecessary fluff while delivering all necessary 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?

The description explains the tool's purpose, workflow, and side effects. It lacks details about error handling or return values, but given the simplicity and the presence of sibling tools, it is sufficiently complete for an agent to use correctly.

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?

The schema already describes session_id as 'Active session ID', but the description adds context that this session is used to provide outline and research context, enhancing the meaning beyond the basic schema.

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 generates complete blog posts based on an outline, with specific steps. It distinguishes itself from sibling tools like generate_outline and save_draft by focusing on full content generation and explicitly referencing the context it provides.

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 usage instructions: review the approved outline and research, write the blog post in markdown, and call save_draft(). This gives a clear workflow for when and how to use the tool.

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