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LimeAI MCP Server

LimeAI MCP Server

by liuwenlonghub
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

save_markdown

Save markdown-formatted text content directly to LimeAI, enabling persistent storage and integration with your workflow.

Instructions

保存文本内容（markdown格式）到 LimeAI

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": {
      "text_content": "<text_content>"
    },
    "name": "save_markdown"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_nameNo
text_contentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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 only states 'save' without disclosing side effects, overwrite behavior, permissions, or return values, leaving the agent with minimal insight into what the operation entails.

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, front-loaded sentence with no filler or redundant details. It appropriately captures the core purpose in minimal space.

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?

There is no output schema or annotations, and the description is too sparse to compensate. It omits the file_name parameter, behavior on save, and clear differentiation from save_html, making it incomplete for reliable invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not mention file_name or elaborate on text_content beyond naming it. It adds no meaning beyond the schema's property names, leaving parameters effectively undocumented.

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 saves text content in markdown format to LimeAI, using a specific verb and resource. It distinguishes this tool from the sibling save_html by explicitly mentioning 'markdown format'.

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 mention of 'markdown format' implicitly suggests this tool is for markdown content, contrasting with save_html, but there is no explicit guidance on when to use this tool versus alternatives or when not to use it.

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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