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mcp-pyright

mcp-pyright

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_hover

Retrieve type information and documentation for Python symbols at specific code positions to understand code structure and functionality.

Instructions

Get hover information at a specific position.

Returns type information and documentation for the symbol at the given position.

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": {
      "code": "<code>",
      "position": "<position>"
    },
    "name": "get_hover"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesPython code as string.
positionYesCharacter position (0-indexed) in the code.
python_pathNoOptional path to Python interpreter.

Output Schema

NameRequiredDescriptionDefault

No arguments

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 full burden. It states the tool returns type information and documentation, but doesn't disclose behavioral traits such as error handling, performance characteristics, or whether it requires specific permissions. The description is minimal and lacks depth for a tool with parameters.

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 very concise with two sentences that directly state the tool's purpose and return value. It is front-loaded and wastes no words, making it efficient and easy to parse.

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?

Given the tool has an output schema (which covers return values) and full schema description coverage, the description is minimally adequate. However, for a tool with no annotations and sibling alternatives, it lacks context on usage and behavioral transparency, making it incomplete for optimal agent understanding.

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 100%, so the schema fully documents the three parameters (code, position, python_path). The description adds no additional meaning beyond what the schema provides, such as examples or usage context for the parameters. Baseline 3 is appropriate since the schema handles parameter documentation.

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 ('Get') and resource ('hover information'), and specifies it returns type information and documentation for symbols. However, it doesn't differentiate from sibling tools like 'get_definition' or 'get_completions' which might provide related information.

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 like 'get_definition' or 'get_completions'. It mentions the tool's function but offers no context about appropriate scenarios, prerequisites, or exclusions.

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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