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Medium Blog MCP Server

Medium Blog MCP Server

by Navneet1710
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Request More Research

request_more_research

Request additional focused research on specific topics for an active blog generation session.

Instructions

Request additional focused research

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>",
      "specific_queries": "<specific_queries>"
    },
    "name": "request_more_research"
  }
}

Input Schema

NameRequiredDescriptionDefault
session_idYesActive session ID
specific_queriesYesList of specific topics to research

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries full responsibility for transparency. It states the intent but does not describe side effects (e.g., whether it triggers a background process), return format, or what happens after the request is made.

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 extremely concise, using only four words to convey the essential action and resource. No unnecessary words or redundancy.

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

Completeness3/5

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

The description is minimal and does not specify the expected output, error conditions, or how it fits into the broader workflow (e.g., whether it updates the session state). Given the tool's simplicity, it is adequate but leaves room for ambiguity about its exact behavior.

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 schema includes clear descriptions for both parameters: session_id as 'Active session ID' and specific_queries as 'List of specific topics to research'. The description adds no extra meaning beyond the schema, so the baseline score of 3 applies.

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 action ('Request') and the resource ('additional focused research'), making its purpose understandable. However, it does not explicitly differentiate itself from sibling tools like 'research_topic' or 'get_research_summary' beyond the word 'additional', which is somewhat implicit.

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

Usage Guidelines3/5

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

The description implies usage when more research is needed after an initial phase, but it does not explicitly state when to use this tool versus alternatives such as 'research_topic' or 'approve_research'. No clear prerequisites or conditions are given.

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

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